Model Context Protocol

Model Context Protocol Developer Jobs

10 jobs found

Today

Delivery Senior Consultant, Software Engineering Solutions, Identity & Gen AI Engineer

Deloitte Atlanta, GA

Atlanta, GA

Today

Full time Agentic Ai Artificial Intelligence Authentication

Apply Now

Job Description

Deloitte is seeking a Delivery Senior Consultant to drive Identity and Gen AI engineering initiatives, building and securing AI solutions that enforce identity, access, and trust across both human and non-human identities and GenAI platforms. This hands-on role blends active engineering, system integration, and ongoing refinement to help clients deploy responsible AI at scale.

Responsibilities

Design, build, and integrate generative AI capabilities such as large language model applications, retrieval-augmented generation, and AI agents, ensuring secure data access and seamless connectivity to downstream systems.
Implement authentication, authorization, and identity controls for AI agents, service accounts, and other non-human identities operating within enterprise and cloud environments.
Establish guardrails for agentic workflows, applying scoped permissions, least-privilege access, credential and secrets management, and runtime policy enforcement.
Set up comprehensive logging, monitoring, and governance to provide traceability and accountability for AI system actions.
Collaborate with IAM, security architecture, and data teams to embed identity controls into GenAI solution delivery and day-to-day operations.
Create and maintain reference architectures, reusable patterns, and thorough technical documentation for building and securing AI systems.

Requirements

Bachelor’s degree in Cybersecurity, Computer Science, Information Systems, Engineering, or a related technical field.
Ability to work onsite up to five days per week.
At least 3 years of software engineering experience with Python or an equivalent language.
Over one year of hands-on experience building, integrating, or deploying generative AI solutions such as LLM applications, retrieval-augmented generation, or AI agents, including use of model APIs, orchestration frameworks, and tools like Claude Code, OpenAI Codex, GitHub Copilot, or Cursor.
Working knowledge of identity and access management concepts and protocols, including authentication, authorization, single sign-on, and standards such as OpenID Connect, SAML, OAuth, and JWT.
Ability to travel about 15 percent on average, depending on client engagements and project needs.
Eligibility to obtain and maintain the necessary security clearance.
Must be legally authorized to work in the United States without the need for employer sponsorship, now or in the future.
Hybrid delivery model requiring residence within a commutable distance to a Deloitte Delivery Center or Geo-Hub location in the United States (examples include Gilbert, Lake Mary, Mechanicsburg, Atlanta, Charlotte, Dallas, Houston, and Philadelphia).
Co-location expectation up to 30 percent of working time for orchestrated opportunities, including projects, training, and Moments That Matter at a Deloitte Delivery Center location, Geo-Hub location, approved site, or project site.
Maximum of 10 percent overnight travel for client or project purposes.
If relocation is necessary, the move must be completed within 12 weeks from the start date to reside within a commutable distance.

Technologies

Python
Claude Code, OpenAI Codex
GitHub Copilot, Cursor
LangChain, LangGraph
Model Context Protocol, Open Policy Agent
Cedar, OpenFGA
HashiCorp Vault, CyberArk, SailPoint, Okta, Microsoft Entra ID
AWS, Microsoft Azure
Terraform, Ansible
OpenID Connect, SAML, OAuth, JWT

View full job page →

6d ago

Delivery Senior Consultant, Software Engineering Solutions, Identity & Gen AI Engineer

Deloitte Philadelphia, PA

Philadelphia, PA

6d ago

Full time Agentic Ai AI Enablement Cloud Solutions

Apply Now

Job Description

Deloitte offers a path into a proactive Cyber team focused on engineering secure generative AI solutions with strong identity, access, and trust controls. This hybrid role in Philadelphia places you alongside IAM, security architecture, and data teams to embed identity into GenAI delivery and operations. Our Deloitte Cyber team helps clients operate with resilience and manage risk through reference architectures, reusable patterns, and clear governance, supporting growth with confidence.

Responsibilities

Build and integrate generative AI solutions, including LLM applications, retrieval-augmented generation, and AI agents, with secure data and downstream system access.
Design authentication, authorization, and identity controls for AI agents, service accounts, and other non-human identities across enterprise and cloud environments.
Create guardrails for agentic workflows, applying scoped permissions, least-privilege access, credential and secrets management, and runtime policy enforcement.
Establish logging, monitoring, and governance to provide traceability and accountability for AI system actions.
Collaborate with IAM, security architecture, and data teams to embed identity controls into GenAI solution delivery and operations.
Develop and maintain reference architectures, reusable patterns, and technical documentation for building and securing AI systems.

Requirements

Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Engineering, or a related technical field
Ability to work onsite up to five days a week
3+ years of software engineering experience with Python or a comparable language
1+ year of hands-on experience building, integrating, or deploying generative AI solutions such as large language model applications, retrieval-augmented generation, or AI agents, including use of model APIs, orchestration frameworks, and AI development tools such as Claude Code, OpenAI Codex, GitHub Copilot, or Cursor
Working knowledge of identity and access management concepts and protocols, including authentication, authorization, single sign-on, and standards such as OpenID Connect, SAML, OAuth, and JSON Web Token
Ability to travel 15% on average, depending on client engagements
Ability to obtain and maintain the necessary security clearance
Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future
Delivery Center Location & Travel Requirements:
- Hybrid work model requiring residence within a commutable distance to one of the US Delivery Center locations (Gilbert, Lake Mary, Mechanicsburg) or Geo-Hub locations (Atlanta, Charlotte, Dallas, Houston, Philadelphia)
- Co-location up to 30% of working time at an assigned office for orchestrated opportunities, including projects, training, and Moments That Matter
- Travel up to 10% overnight for client or project purposes
- Relocation, if necessary, to be completed within 12 weeks from the start date to reside within a commutable distance
Preferred:

Experience deploying generative AI solutions to production environments
Hands-on experience with identity and access management platforms such as SailPoint, Okta, or Microsoft Entra ID
Experience securing non-human identities, service accounts, secrets, and credentials using HashiCorp Vault or CyberArk
Experience with AI agent frameworks and protocols such as LangChain, LangGraph, or Model Context Protocol
Experience with fine-grained authorization or policy-as-code using Open Policy Agent, Cedar, or OpenFGA
Familiarity with AI security risks, including OWASP Top 10 for LLM Applications, prompt injection, and excessive agency
Experience applying AI governance and risk frameworks such as the NIST AI RMF
2+ years of building or deploying workloads in AWS and Microsoft Azure
Certifications such as CISSP, CCSP, or cloud-focused credentials (e.g., AWS Solutions Architect, Azure Solutions Architect)
1+ year of experience supporting federal government environments
1+ year of experience with infrastructure-as-code or automation technologies such as Terraform or Ansible

View full job page →

8d ago

Lead Principal Machine Learning Engineer

Oracle Seattle, WA

Seattle, WA

8d ago

Full time Ai Ml Ai Platform Artificial Intelligence

Apply Now

Job Description

Lead Principal Machine Learning Engineer at Oracle in Seattle, onsite, responsible for defining, building, and operating production-grade agentic AI platforms on Oracle Cloud Infrastructure.

Responsibilities

Act as the senior technical owner of OCI AI platform capabilities, overseeing agent execution, inference systems, model serving, AI workflow orchestration, evaluation, and observability.
Design and deliver scalable agentic AI systems that reason, plan, use tools, execute workflows, orchestrate multi-step tasks, and enable safe human-in-the-loop escalation.
Develop production-grade services for tool invocation, agent memory, context management, Model Context Protocol integration, vector retrieval, multi-agent coordination, policy enforcement, and evaluation.
Steer architecture across distributed services optimized for low latency, high throughput, GPU efficiency, reliability, cost, operability, and secure multi-tenant operation.
Define service boundaries, APIs, data models, state management, consistency tradeoffs, failure modes, SLIs/SLOs, rollout strategies, and readiness criteria for AI platform services.
Drive technical strategy across infrastructure, platform, security, data, and application engineering teams, translating broad goals into multi-quarter plans and milestones.
Integrate AI agents securely and reliably with enterprise APIs, cloud services, databases, identity systems, secrets management, and external systems.
Establish AgentOps and LLMOps practices for tracing, monitoring, evaluation suites, regression testing, experimentation, safety guardrails, prompt and tool versioning, and production reliability.
Evaluate and operationalize emerging technologies in generative AI, agentic workflows, inference optimization, long-context systems, reasoning models, AI developer tooling, and agentic-first development.
Promote engineering excellence through code and design reviews, test strategy, deployment automation, incident analysis, documentation, and AI assisted development using tools like Codex, Claude Code, Cursor, Copilot, or similar.
Mentor staff and senior engineers, raise architectural standards, and influence OCI engineering practices without requiring direct management authority.
Own critical production outcomes including reliability, performance, security posture, cost efficiency, and supportability of the systems delivered.

Requirements

Bachelor's, Master's, or PhD in Computer Science, AI/ML, Engineering, or related field, or equivalent practical experience.
12+ years of professional software engineering experience with substantial ownership of production systems, or equivalent Senior Staff / Principal level impact.
Proven track record as Staff, Senior Staff, Principal, or equivalent technical leader influencing architecture and execution across multiple teams.
Deep experience designing, building, and operating high-scale distributed systems, cloud services, infrastructure platforms, or AI/ML platform services.
Hands-on experience with production AI systems, agentic AI applications, autonomous workflows, tool-using agents, multi-step orchestration, or multi-agent systems.
Practical experience with orchestration frameworks such as LangGraph, LangChain, CrewAI, AutoGen, LlamaIndex, or similar ecosystems.
Deep understanding of LLM application patterns, including prompt design, structured outputs, function/tool calling, context management, RAG, memory, tool safety, and evaluation.
Strong Python programming skills with ability to contribute production-grade code, reviews, tests, and debugging in complex distributed environments.
Strong expertise with Kubernetes, Docker, cloud-native infrastructure, service-to-service communication, scalability, fault tolerance, observability, and performance analysis.
Experience defining SLIs/SLOs, production readiness criteria, incident response practices, monitoring, tracing, experiments, and reliability programs for AI or distributed systems.
Solid understanding of AI safety, governance, security, and operational risks for autonomous or semi-autonomous systems, including data handling, access control, auditability, and human accountability.
Excellent written and verbal communication with demonstrated ability to lead technical direction, resolve ambiguity, and influence senior stakeholders.

Technologies

Oracle Cloud Infrastructure (OCI)
Python
Kubernetes
Docker
LangGraph
LangChain
CrewAI
AutoGen
LlamaIndex
Model Context Protocol (MCP)
Codex
Claude Code
Cursor
Copilot

View full job page →

8d ago

Principal AI Developer

Energy Transfer Partners Houston, TX

Houston, TX

8d ago

Full time Backend Developer Python Agentic Ai

Apply Now

Job Description

Energy Transfer Partners is seeking a hands-on Principal AI Developer based in Houston, TX (onsite) to lead production AI initiatives within the Enterprise AI team. You will design, build, deploy, and iterate AI solutions using Python or .NET, Azure, and modern data tooling, partnering with AI engineers and business analysts to turn experiments into production systems that scale.

Responsibilities

Design, implement, deploy, and maintain AI solutions using Python and/or .NET.
Create AI agents via Microsoft Copilot Studio or the Semantic Kernel Agent Framework.
Develop and optimize cloud-native applications on Azure.
Work with large-scale data in Databricks.
Collaborate with AI engineers and business analysts to translate ideas into production systems.
Apply critical thinking to evaluate model performance, troubleshoot complex issues, and improve system efficiency.
Communicate clearly with both technical and non-technical stakeholders.
Prototype quickly, test rigorously, and iterate often.

Requirements

Bachelor’s degree or equivalent experience, with level-appropriate experience commensurate with the job level.
Professional experience building production systems with Python or .NET (proficiency in both is a strong plus).
Solid working knowledge of cloud services and architecture patterns, with Azure preferred (or equivalent AWS/GCP experience and willingness to ramp on Azure).
Hands-on experience building Retrieval-Augmented Generation (RAG) pipelines.
Hands-on experience building AI agents with Microsoft Copilot Studio, Semantic Kernel Agent Framework, or an equivalent agent framework (e.g., LangGraph, AutoGen, CrewAI).
Hands-on experience with at least two of the following: Azure AI Search (or equivalent vector/semantic search platform), vector databases, semantic search, agentic AI systems.
Comfort working with SQL and large-scale data platforms; Databricks experience is a plus, with approachable SQL syntax.
Excellent communication and critical-thinking skills.
Background in a smaller company or startup environment with substantial ownership of technical work.

Experience levels

Senior Specialist: Bachelor’s degree or equivalent experience and 5-8 years of relevant job-related experience.
Lead Specialist: Bachelor’s degree or equivalent experience and 8+ years of relevant job-related experience.
Principal Specialist: Bachelor’s degree or equivalent experience and 10+ years of relevant job-related experience.

Technologies

Python
.NET
Azure (including Azure OpenAI, Azure AI Foundry, Azure AI Search)
Databricks
Microsoft Copilot Studio
Semantic Kernel
Vector databases and semantic search (Pinecone, Weaviate, pgvector, Elasticsearch with vector, etc.)
RAG (Retrieval-Augmented Generation)
Agentic AI concepts and tool orchestration
MCP (Model Context Protocol) and related agent tooling
LangGraph, AutoGen, CrewAI
SQL; experience with Databricks is a plus

Benefits

Industry leading compensation
Comprehensive benefits
401(k) match with additional profit sharing
PTO
Abundant career opportunities

Working Conditions

On-site role in the office five days per week during business hours.
Must be able to remain in a stationary position for roughly 50% of the time due to prolonged periods of sitting or standing.
Occasional overnight travel to other company locations may be required.

View full job page →

11d ago

Delivery Senior Consultant, Software Engineering Solutions, Identity & Gen AI Engineer

Deloitte Gilbert, AZ

Gilbert, AZ

11d ago

Full time Agentic Ai Artificial Intelligence Cloud Operations

Apply Now

Job Description

Responsibilities

Build and integrate generative AI solutions, including large language model applications, retrieval-augmented generation, and AI agents, with secure access to data and downstream systems.
Engineer authentication, authorization, and identity controls for AI agents, service accounts, and other non-human identities operating across enterprise and cloud environments.
Develop guardrails for agentic workflows, including scoped permissions, least-privilege access, credential and secrets management, and runtime policy enforcement.
Implement logging, monitoring, and governance that provide traceability and accountability for AI system actions.
Collaborate with IAM, security architecture, and data teams to embed identity controls into GenAI solution delivery and operations.
Create and maintain reference architectures, reusable patterns, and technical documentation for building and securing AI systems.

Requirements

Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Engineering, or a related technical field
Ability to work onsite up to five days a week
3+ years of software engineering experience with Python or a comparable language
1+ year of hands-on experience building, integrating, or deploying generative AI solutions such as LLM applications, retrieval-augmented generation, or AI agents, including use of model APIs, orchestration frameworks, and AI development tools such as Claude Code, OpenAI Codex, GitHub Copilot, or Cursor
Working knowledge of identity and access management concepts and protocols, including authentication, authorization, single sign-on, and standards such as OpenID Connect, SAML, OAuth, and JWT
Ability to travel 15% on average, based on the work and client needs
Ability to obtain and maintain the necessary security clearance
Legally authorized to work in the United States without the need for employer sponsorship now or in the future
Hybrid work model requiring residence within a commutable distance to a Deloitte Delivery Center location (Gilbert, Lake Mary, Mechanicsburg) or Geo-Hub locations (Atlanta, Charlotte, Dallas, Houston, Philadelphia); up to 30% time co-located
Travel up to 10% overnight for client or project purposes
If relocation is necessary, complete the move within 12 weeks from the start date

Technologies

Python
Claude Code
OpenAI Codex
GitHub Copilot
Cursor
LangChain
LangGraph
Model Context Protocol (MCP)
Open Policy Agent (OPA)
Cedar
OpenFGA
AWS
Microsoft Azure
Terraform
Ansible
SailPoint
Okta
Microsoft Entra ID
HashiCorp Vault
CyberArk
OpenID Connect (OIDC)
SAML
OAuth
JSON Web Token (JWT)

View full job page →

13d ago

Delivery Senior Consultant, Software Engineering Solutions, Identity & Gen AI Engineer

Deloitte Lake Mary, FL

Lake Mary, FL

13d ago

Full time Senior AI Consultant

Apply Now

Job Description

Role focused on securing GenAI deployments through identity, access controls, and governance across enterprise ecosystems.

Responsibilities

Design and integrate GenAI capabilities, including LLM applications, retrieval augmented generation workflows, and AI agents, with secure data access and smooth integration to downstream systems.
Develop authentication, authorization, and identity controls for AI agents, service accounts, and other non-human identities operating across on premise and cloud environments.
Create guardrails for agent driven workflows, including scoped permissions, least privilege access, secrets management, and runtime policy enforcement.
Establish comprehensive logging, monitoring, and governance to ensure traceability and accountability of AI system actions.
Collaborate with IAM, security architecture, and data teams to embed identity controls into GenAI solution delivery and operations.
Develop and maintain reference architectures, reusable patterns, and technical documentation for building and securing AI systems.

Requirements

Bachelor's degree in cybersecurity, computer science, information systems, engineering, or a closely related technical field.
Willingness to work onsite up to five days per week.
Minimum 3+ years of software engineering experience with Python or a comparable language.
At least 1+ year of hands on experience building, integrating, or deploying generative AI solutions such as LLM applications, RAG, or AI agents, including use of model APIs, orchestration frameworks, and tools such as Claude Code, OpenAI Codex, GitHub Copilot, or Cursor.
Solid knowledge of identity and access management concepts and protocols, including authentication, authorization, SSO, and standards such as OIDC, SAML, OAuth, and JWT.
Ability to travel on average 15% based on client engagements.
Ability to obtain and maintain the necessary security clearance.
legally authorized to work in the United States without employer sponsorship now or in the future.
Hybrid work model requiring residence within a commutable distance to one of the US Delivery Center locations (Gilbert, Lake Mary, Mechanicsburg) or Geo-Hub locations (Atlanta, Charlotte, Dallas, Houston, Philadelphia).
Up to 30% of working time may be co located at an assigned office for opportunities such as projects, training, and practice sessions at Deloitte Delivery Centers, Geo Hub locations, approved sites, or project locations.
Up to 10% overnight travel for client or project purposes.
If relocation is necessary, complete the move within 12 weeks to reside within a commutable distance.

Technologies

Python
Claude Code
OpenAI Codex
GitHub Copilot
Cursor
LangChain
LangGraph
Model Context Protocol (MCP)
Open Policy Agent (OPA)
Cedar
OpenFGA
HashiCorp Vault
CyberArk
SailPoint
Okta
Microsoft Entra ID
AWS
Microsoft Azure
Terraform
Ansible
OIDC
SAML
OAuth
JWT
Retrieval augmented generation (RAG)
Large language model (LLM)

View full job page →

23d ago

Lead Principal Machine Learning Engineer

Oracle San Francisco, CA

San Francisco, CA

23d ago

Full time Senior Agent Orchestration AI

Apply Now

Job Description

Oracle in San Francisco is seeking a senior principal machine learning engineer to define, build, and operate next-generation AI systems on Oracle Cloud Infrastructure (OCI). This hands-on technical leader will set the architecture and engineering direction for production-grade agentic AI platforms, autonomous workflows, scalable inference infrastructure, and enterprise AI applications used in large-scale, business-critical environments.

Responsibilities

Serve as a senior technical owner for OCI AI platform capabilities, including agent execution, inference systems, model serving, AI workflow orchestration, evaluation, and observability.
Design, architect, and deliver scalable agentic AI systems capable of reasoning, planning, tool use, workflow execution, multi-step task orchestration, and safe human-in-the-loop escalation.
Build production-grade services for tool calling, agent memory, context management, Model Context Protocol (MCP) integration, vector retrieval, multi-agent coordination, policy enforcement, and evaluation.
Lead architecture across distributed services optimized for low latency, high throughput, GPU efficiency, reliability, cost, operability, and secure multi-tenant operation.
Define service boundaries, APIs, data models, state management, consistency tradeoffs, failure modes, SLIs/SLOs, rollout strategies, and operational readiness criteria for AI platform services.
Drive technical strategy across infrastructure, platform, security, data, and application engineering teams, converting broad goals into executable multi-quarter plans and measurable milestones.
Integrate AI agents securely and reliably with enterprise APIs, cloud services, databases, identity systems, secrets management, and external systems.
Establish AgentOps and LLMOps practices for tracing, monitoring, eval suites, regression testing, experimentation, safety guardrails, prompt/tool versioning, and production reliability.
Evaluate and operationalize emerging technologies in generative AI, agentic workflows, inference optimization, long-context systems, reasoning models, AI developer tooling, and agentic-first development.
Drive engineering excellence through code reviews, design reviews, test strategy, deployment automation, incident analysis, documentation, and AI-assisted development practices using tools such as Codex, Claude Code, Cursor, Copilot, or similar systems.
Mentor staff and senior engineers, raise architectural standards, and influence engineering practices across OCI without requiring direct management authority.
Own critical production outcomes, including reliability, performance, security posture, cost efficiency, and supportability for the systems delivered.

Requirements

Bachelor's, Master's, or Ph.D. in Computer Science, AI/ML, Engineering, or a related field, or equivalent practical experience.
12+ years of professional software engineering experience, including significant ownership of production systems; or equivalent experience demonstrating senior staff / principal-level impact.
Proven track record as a Staff, Senior Staff, Principal, or equivalent technical leader influencing architecture and execution across multiple teams.
Deep experience designing, building, and operating high-scale distributed systems, cloud services, infrastructure platforms, or AI/ML platform services.
Hands-on experience with production AI systems, agentic AI applications, autonomous workflows, tool-using agents, multi-step orchestration, or multi-agent systems.
Practical experience with orchestration frameworks such as LangGraph, LangChain, CrewAI, AutoGen, LlamaIndex, or similar ecosystems.
Deep understanding of LLM application patterns, including prompt design, structured outputs, function/tool calling, context management, RAG, memory, tool safety, and evaluation.
Strong programming skills in Python and ability to contribute high-quality production code, reviews, tests, and debugging in complex distributed environments.
Strong expertise with Kubernetes, Docker, cloud-native infrastructure, service-to-service communication, scalability, fault tolerance, observability, and performance analysis.
Experience defining SLIs/SLOs, production readiness criteria, incident response practices, monitoring, tracing, experiments, and reliability programs for AI or distributed systems.
Strong understanding of AI safety, governance, security, and operational risks for autonomous or semi-autonomous systems, including data handling, access control, auditability, and human accountability.
Excellent written and verbal communication, with demonstrated ability to lead technical direction, resolve ambiguity, and influence senior stakeholders.

Technologies

Python
Kubernetes
Docker
LangGraph
LangChain
CrewAI
AutoGen
LlamaIndex
Model Context Protocol (MCP)
Oracle Cloud Infrastructure (OCI)
Codex
Claude Code
Cursor
Copilot

Preferred Qualifications

Experience optimizing large-scale GPU inference or training workloads for latency, throughput, utilization, availability, and cost.
Experience building or operating model serving, inference gateways, agent runtimes, workflow engines, developer platforms, or internal AI productivity platforms.
Experience integrating AI systems with enterprise APIs, databases, cloud services, vector databases, embeddings, retrieval systems, identity systems, and policy enforcement layers.
Experience with LLM fine-tuning, long-context systems, reasoning models, model routing, caching, batching, quantization, or emerging generative AI research.
Experience building evaluation frameworks for agentic systems, including offline evals, online experiments, golden tasks, adversarial testing, regression gates, and observability dashboards.
Experience using AI-assisted software development tools such as Codex, Claude Code, Cursor, Copilot, or similar systems in large-scale engineering environments.
Track record of defining architectural standards, platform capabilities, or engineering practices adopted across multiple teams or organizations.
Experience in enterprise, cloud infrastructure, regulated, security-sensitive, or mission-critical environments.