Description

Core Focus: Building AI‑enabled applications + full stack development

• Experience building full stack apps (React/Angular/Vue + Node.js/Python/Java backend)
• Strong Python skills for AI workflows (FastAPI, LangChain, LlamaIndex)
• Hands-on experience with LLMs (OpenAI, Claude, Gemini, Amazon Bedrock)
• Experience implementing RAG pipelines (vector stores, embeddings, hybrid search)
• Ability to integrate LLM orchestration layers, agents, and structured output generation
• Experience with LLMOps (model lifecycle, telemetry, evaluation, CI/CD for models)
• Cloud-native AI deployment (AWS Lambda, S3, ECS/EKS, API Gateway)
• Experience with document processing, intelligent search, NLP-driven workflows
• Ability to work with data scientists on fine-tuning or evaluating models
• Strong DevOps background (GitLab/GitHub CI/CD, Docker, Kubernetes)
• Understanding of responsible AI, security, and federal compliance (508, Public Trust)

Mindset: Full Stack AI Engineers build intelligent systems, not just APIs — they combine software engineering + applied AI + cloud + frontend.

Overview: This role blends hands-on software engineering, applied AI, cloud-native development, and integration of generative AI accelerators into mission systems.

Job Description:

• Design, develop, and deploy AI-enabled full stack applications that support document processing, intelligent search, generative AI use cases, and agentic workflows.
• Implement and integrate reusable AI accelerators such as RAG pipelines, model orchestration layers, hybrid search components, and structured data generation capabilities.
• Develop secure, cloud-native backend APIs and microservices (preferably AWS-based), data ingestion, and workflow automation.
• Collaborate with data scientists to train, fine-tune, or evaluate machine learning and LLM models implemented within client systems.
• Apply LLMOps best practices for model lifecycle, experimentation, telemetry, CI/CD, testing, and monitoring.
• Ensure solutions comply with client security requirements, federal accessibility standards, and responsible AI principles.
• Support rapid prototyping as well as hardening prototypes to production-grade systems aligned to client modernization initiatives (e.g., intelligent document management, NLP-driven search, cloud migration).
• Participate in sprint ceremonies, backlog refinement, and joint design sessions with product owners and technical leads.
• Produce documentation, architecture diagrams, and deployment artifacts.

Required Qualifications:

• Experience building full stack applications using frameworks such as React, Angular, or Vue; and backend frameworks such as Node.js, Python FastAPI, or Java Spring.
• Hands-on experience applying machine learning or LLM capabilities in production or near-production environments.
• Strong Python skills for AI workflows and API development.
• Experience with AWS services (e.g., Lambda, S3, ECS/EKS, API Gateway, CloudFormation/Terraform).
• Familiarity with vector search, embeddings, RAG architectures, or NLP/LLM-driven systems.
• Experience with DevOps tooling (GitLab/GitHub CI/CD, Docker, Kubernetes).
• Ability to work directly with clients, refine requirements, and deliver iterative prototypes quickly.
• Ability to successfully complete a Public Trust investigation

Key Skills

Education

Any Graduate