Sme Developer Jobs

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6d ago

Lead AWS Software Engineer (AI and DevOps SME)

Fannie Mae Reston, VA

Reston, VA

6d ago

$141k - $184k/yr Full time AI AWS DevOps

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Job Description

Benefits

Health benefits
Life insurance
Voluntary lifestyle benefits
Other benefits and perks

Responsibilities

Assess customer requirements autonomously, identifying and reconciling conflicting or complementary needs across stakeholder groups.
Leverage deep expertise to design and develop software solutions that address customer needs.
Lead design work using a structured, process driven approach.
Roll out new software technologies and coordinate concurrent implementation tasks across teams.
This position has a single opening and is based in the Reston, VA office.

Requirements

Four years of experience in software engineering, preferably within financial services.
Proficient in Python and SQL with AWS experience.
Four years of DevOps engineering experience.
Two to three years in AI/ML engineering roles.
Understanding of financial data, KPIs, and reporting standards.
Excellent communication and collaboration skills.
Bachelor's degree in a related field is required.

Technologies

AWS
Python
SQL
REST
SOAP
FastAPI
React
Angular
JavaScript
TypeScript
AJAX
HTML5
CSS3
Streamlit
Terraform
CloudFormation
Docker
Kubernetes (EKS)
Infrastructure-as-Code (IaC)
Jenkins
GitHub Actions
GitLab CI
AWS DevOps services
AWS CloudWatch
Splunk
LangChain
LangGraph
AI agents
RAG frameworks
Vector databases
Embedding models
MCP integrations
Power BI
Tableau

Impact you will make

The Lead AWS Software Engineer (AI and DevOps SME) role offers flexibility and a collaborative environment to deliver on the responsibilities described above.

The Experience You Bring to the Team

Minimum Required Experiences

4 years overall in software engineering, preferably in financial services.
Programming skills in Python, SQL and experience with AWS.
4 years DevOps engineering experience.
2-3 years of experience in AI/ML engineering roles.
Understanding financial data, KPIs, and reporting standards.
Excellent communication and collaboration skills.

Desired Experiences

Experience in finance or fintech with exposure to building and managing Risk Management and Audit applications
Experience with data visualization tools such as Power BI or Tableau

AWS and Cloud Engineering

Experience leveraging AWS cloud services to design, develop, and support scalable, cloud-native enterprise applications and data platforms.
Strong expertise in Python, SQL, and AWS for developing cloud-native applications, data pipelines, and scalable enterprise solutions.
Designed and integrated enterprise applications using REST, SOAP, and Fast API services, enabling secure, scalable, and high-performance system-to-system communication.
Experience developing modern web applications and user interfaces using React, Angular, JavaScript, TypeScript, AJAX, HTML5, CSS3, and Streamlit.
Built responsive dashboards, reporting applications, and data visualization solutions with seamless backend API integrations.
Developed reusable UI components and modern frontend design practices to improve usability and performance.
Developed ETL workflows and data pipelines for analytics, reporting, model training, and business intelligence.
Analyzed financial and business data using Python and SQL, collaborating with cross-functional stakeholders and improving model performance and governance.

AI and Machine Learning

AI/ML and Generative AI engineering experience delivering GenAI powered assistants, intelligent automation, AI-driven workflows, and decision-support solutions.
Developed enterprise GenAI solutions using LangChain, LangGraph, AI agents, RAG frameworks, vector databases, embedding models, and MCP integrations.
Applied prompt engineering and LLM optimization techniques for financial reporting, document summarization, intelligent search, client communications, and workflow automation.
Built and orchestrated multi-agent workflows, tool-calling frameworks, and retrieval pipelines to improve AI reasoning and response accuracy.
Authored model documentation, prompt strategies, and governance artifacts to support audit and compliance needs.

DevOps and CI/CD

DevOps engineering experience implementing CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, and AWS DevOps services.
Automated infrastructure provisioning and deployments using Terraform, CloudFormation, Docker, Kubernetes (EKS), and IaC practices.
Integrated DevSecOps controls, automated testing, code quality validation, and security scanning to improve reliability and compliance.
Implemented monitoring, logging, and observability with AWS CloudWatch and Splunk, supporting lifecycle management of applications and AI models.

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