AI Developer

UNAVAILABLE; McLean (VA); On-site; USD 140,000 - 210,000; Full time

Job summary

UNAVAILABLE is seeking a highly skilled AI Developer to design, build, and optimize advanced AI solutions in predictive, generative, and autonomous domains. You will work end-to-end from data ingestion to deployment, collaborating with product teams and mission stakeholders in a highly technical environment.

You will mentor engineers, implement secure-by-design practices, and stay current with foundation models, agent frameworks, and evaluation tools to continuously improve delivery quality.

Qualifications

• Bachelor's degree and 5 years of relevant experience; OR Master’s degree and 3 years; OR No degree and 9 years of relevant experience.
• Proficiency in Python; comfortable with the AI/ML tooling ecosystem.
• Strong prompt engineering skills and system prompts, few-shot design, and iterative refinement.
• Experience containerizing and deploying apps with Docker.

Responsibilities

• Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi-agent workflows, RAG pipelines, and microservices.
• Implement reusable AI components, libraries, and APIs to accelerate delivery across programs.
• Integrate AI models with enterprise systems, APIs, data platforms, vector stores, and cloud-native services.
• Design and implement advanced prompt strategies, context management, retrieval systems, and LLM orchestration logic.
• Build scalable inference services, optimize model performance, and collaborate with LLMOps for deployment and monitoring.
• Mentor junior developers, conduct code reviews, and support engineering excellence.

Skills

Python

LLM orchestration

RAG architectures

Docker

Git

REST APIs

Prompt engineering

AWS

Vector databases

Education

Bachelor's degree

Master's degree

No degree with 9 years experience

Tools

LangChain

LlamaIndex

LangGraph

CrewAI

Job description

Overview

We're looking for a highly skilledAI Developer to design, build, and optimize advanced AI solutions across predictive, generative, and autonomous system domains. This role requires strong hands-on engineering capabilities, deep familiarity with modern AI architectures, and the ability to translate mission needs into robust, production-ready AI capabilities. The Senior AI Developer will work across the full stack of AI development, from data ingestion and model experimentation to application integration, orchestration, and deployment, and will collaborate closely with product teams, LLMOps engineers, designers, and mission stakeholders.

Responsibilities

• Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi-agent workflows, RAG pipelines, and specialized AI microservices.
• Implement reusable AI components, libraries, and APIs that streamline application development and accelerate delivery across programs.
• Integrate AI models with enterprise systems, APIs, data platforms, vector databases, and cloud-native services to deliver scalable mission capabilities.
• Drive iterative experimentation, prototyping, and model improvement cycles in collaboration with Data Scientists and AI Evaluation Scientists.
• Design and implement advanced prompt strategies, context management layers, retrieval systems, and LLM orchestration logic.
• Build scalable inference services, optimize model performance, and collaborate with LLMOps to enable robust deployment, monitoring, and continuous improvement.
• Translate user needs and mission workflows into intuitive, reliable AI-powered features through active partnership with designers and product teams.
• Implement secure-by-design and trustworthy AI practices, including safety guardrails, input sanitization, content filtering, and integration of evaluation metrics.
• Contribute to internal AI frameworks, code patterns, and shared accelerators that raise delivery quality across the AI & Data Exploitation Practice.
• Mentor junior developers, conduct code reviews, and support engineering excellence across multi-disciplinary AI delivery teams.
• Stay current with emerging AI techniques, libraries, foundation models, and agent frameworks, evaluating their applicability to client missions.
• You will contribute to the growth of our AI & Data Exploitation Practice!

Qualifications

• Ability to hold a position of public trust with the U.S. government.
• Bachelor's degree and 5 years of relevant experience; OR
  • Master's degree and 3 year of relevant experience; OR
  • No degree and 9 years of relevant experience.
• Proficiency in Python; comfortable working across the AI/ML tooling ecosystem
• Solid understanding of RAG architectures - chunking strategies, embedding models, vector stores, retrieval evaluation
• Experience with at least one LLM orchestration framework (LangChain, LlamaIndex, LangGraph, CrewAI, or equivalent)
• Strong prompt engineering skills - system prompts, few-shot design, chain-of-thought, and iterative refinement
• Experience containerizing and deploying applications with Docker
• Proficiency with Git and collaborative version control workflows
• Ability to read and write REST APIs; comfortable integrating third-party services and models
• Strong communication skills - you will interact with clients and translate fuzzy requirements into working systems
• Ability to hold a position of public trust with the U.S. government.

Preferred

• Experience with cloud-native AI services, particularly AWS Bedrock for managed LLM inference
• Familiarity with serverless compute (AWS Lambda) and managed ETL pipelines (AWS Glue) for data ingestion workflows
• Working knowledge of vector and relational data stores including AWS RDS Postgres (pgvector) and OpenSearch
• Container orchestration experience with Kubernetes for deploying and scaling AI services
• CI/CD pipeline experience with Jenkins or similar build orchestration tools
• Observability and logging experience for LLM pipelines - LangSmith, Arize, or equivalent
• Familiarity with LLM evaluation frameworks such as RAGAS or DeepEval for measuring RAG and model quality

• • Hands-on experience with workflow automation platforms - n8n, Prefect, Airflow, or similar
  • Experience with MCP and tool-serving infrastructure (MCPO or similar)
  • Experience designing multi-agent systems with agent-to-agent coordination patterns
  • Experience with graph databases (Neo4j, Memgraph) and Graph RAG approaches
  • Prior consulting, agency, or client-delivery experience