Senior Application Engineer

Senior Application Engineer – AI Venture Studio We build secure cloud‑hosted AI applications that empower teams across R&D, Commercialization, Manufacturing, and Enabling Functions. The role requires hands‑on construction of backend services, APIs, agent runtimes, and infrastructure patterns to enable rapid AI Accelerator cycles. Key Responsibilities Design, build, and operate backend services, APIs, and application components for AI Accelerator products. Develop Python/FastAPI or TypeScript/Node services that integrate LLM APIs, retrieval systems, workflow engines, and enterprise systems. Execute six two‑week sprints per 12‑week cycle, delivering, testing, and validating cloud and agentic AI product increments. Build MCP‑accessible services for reading, writing, searching, and maintaining structured knowledge assets. Implement secure application patterns: authn/authz, BMS SSO, secrets management, auditability, input validation, and service boundaries. Partner with frontend engineers to define clean API contracts, streaming response patterns, and error handling. Build and host agentic workflows using LangGraph, including multi‑agent orchestration and durable checkpoints. Integrate retrieval, memory, and context services with AWS‑aligned data stores. Create the semantic layer for natural‑language‑to‑code agents and expose query history and governed data. Package reusable deployment patterns for AWS Fargate, serverless, containers, and production‑ready AI applications. Maintain CI/CD pipelines, infrastructure‑as‑code, automated tests, and observability using LangSmith or similar tools. Embed automated quality gates and responsible AI guardrails in delivery pipelines. Demonstrate MVP progress in bi‑weekly demos and track platform performance, cost, security, and business‑value signals. Collaborate with AI Engineers, Data Engineers, Data Scientists, Frontend Engineers, and product teams to refine priorities and solve delivery challenges. Provide technical coaching through design reviews, code reviews, and documentation. Required Qualifications Bachelor’s degree or higher in Computer Science, Engineering, Science, or related field. 5+ years of experience in software, cloud, platform, or backend application development. Hands‑on experience building cloud‑native applications on AWS (S3, RDS, Athena, ElastiCache, OpenSearch, Fargate, Lambda, IAM, VPC). Strong proficiency in Python/FastAPI or TypeScript/Node, and experience with containers, CI/CD, GitHub workflows, container registries, and infrastructure‑as‑code (Terraform, CDK, or CloudFormation). Experience developing LLM, RAG, or agentic AI applications using LangGraph, LangChain, Pydantic, or similar frameworks. Familiarity with MCP or FastMCP read‑write‑search APIs, vector databases, knowledge graphs, and structured output validation. Experience with SQL, semantic layers, and translating unstructured scientific or operational sources into governed data contexts. Hands‑on integration with model providers and approved frontier LLM models (OpenAI, Anthropic, Gemini, AWS Bedrock). Knowledge of sandboxed execution, provenance, version control, and access‑control patterns for agentic applications. Strong communication skills and ability to work in fast‑moving, cross‑functional agile teams. Benefits Health coverage: Medical, pharmacy, dental, and vision care. Well‑being programs and employee assistance. 401(k) plan, disability insurance, and life insurance. Paid time off, flexible work hours, and optional vacation days. Global shutdown and other time‑off options for eligible employees. Additional incentive cash and stock opportunities (subject to eligibility). Compensation Base salary ranges: CambridgeCrossing – $151,280–$183,319; Madison, Princeton – $137,530–$166,654; Seattle – $151,280–$183,319. Final pay will be determined based on experience and eligibility for incentive programs. #J-18808-Ljbffr