Senior AI Engineer at IPTA in Austin, TX, USA

Job description

• As a Senior AI Engineer, you are at the heart of our team's AI mission. You will architect, build, and deploy production-grade Generative AI applications, autonomous agent workflows, and retrieval-augmented generation (RAG) systems for Army decision support products.
• This is not a traditional ML modeling role, nor is it merely an LLMOps coding position. We require an engineer who possesses a deep theoretical and practical understanding of Foundation Models (FMs), reasoning architectures, and the mechanics underpinning modern AI systems. You will focus on operationalizing FMs, wiring deterministic software systems to non-deterministic LLM reasoning engines, and integrating these nodes directly into data transformation, visualization, and business process pipelines.
• Working alongside a dedicated mission team, you will take ownership of the AI architecture and AI Ops for your projects to ensure our systems meet strict operational standards where accuracy is the highest priority, followed by speed, and then cost.

Responsibilities

• Agentic System Architecture: Design and orchestrate multi-step autonomous AI agents primarily using Palantir AIP. Apply deep theoretical knowledge to implement reliable function calling, state machines, and human-in-the-loop (HITL) checkpoints
• Theoretical & Applied Architecture: Serve as the team's intellectual lead on modern AI systems. Translate the underlying theory of attention mechanisms, vector embeddings, and reasoning frameworks into practical, production-ready software architecture
• Deterministic-Stochastic Bridging: Architect resilient stateful backends that safely wrap probabilistic LLM outputs with deterministic validation, retry policies, strict JSON/Pydantic schemas, and structured error handling
• RAG & Pipeline Integration: Build and scale production RAG pipelines across structured and unstructured Army datasets. Implement hybrid search, advanced chunking, metadata filtering, and re-ranking layers to feed directly into decision support products and visualizations within Foundry
• AI Ops & Evaluation (LLMOps): Take complete ownership of project LLMOps. Implement automated regression testing and continuous evaluation pipelines for LLM outputs (e.g., faithfulness, semantic relevancy, hallucination detection) to guarantee deterministic accuracy
• Safety, Security & Governance: Enforce guardrails around context boundaries, data isolation, multi-tenant RBAC, PII redaction, and mitigation against prompt injection/model evasion within a secure DoD environment
• Performance & Cost Optimization: Manage context window budgets, token consumption metrics, latency profiling, and model routing strategies, strictly adhering to the priority matrix of Accuracy > Speed > Cost

Requirements

• Security Clearance: Must hold a current, active DoD Secret clearance
• Theoretical & Systems Depth: Deep theoretical and practical understanding of Generative AI architectures, foundation models, context management, and advanced prompt engineering (e.g., Chain-of-Thought reasoning)
• Enterprise AI Experience: Proven experience building ontology-driven workflows or AI pipelines within Palantir Foundry, Palantir Maven, or other mature production systems. (Note: Extensive Army Vantage experience is not strictly required if you possess strong analogous production experience)
• Programming & Systems Integration: 5+ years of experience with advanced proficiency in Python and TypeScript, featuring strong software engineering fundamentals (OOP, microservices, async programming, API design)
• Agentic Framework Proof Points: Strong working knowledge of frameworks such as LangChain and LangGraph. While Palantir AIP is the primary platform, experience with these frameworks serves as a critical proof point of your architectural capabilities and will support future needs
• Vector Search & Data Engineering: Proven experience indexing and querying vector databases/extensions (e.g., pgvector, OpenSearch, Pinecone, Qdrant) alongside relational and document datastores
• Evaluation & Observability: Practical experience using LLM tracing and evaluation tools (e.g., Langfuse, Arize Phoenix, Ragas, TruLens) to diagnose multi-turn agent failures and latency bottlenecks
• Active Top Secret (TS) Clearance
• Experience operating within DoD Impact Level 5/6 (IL5/IL6) secure network environments
• Industry Certifications: Recognized applied AI certifications (e.g., Google Cloud Professional Machine Learning Engineer/Generative AI Developer, Claude Architect, AWS Certified Generative AI Developer - Professional, Microsoft Azure AI Engineer Associate)
• Cloud & Infrastructure: Demonstrated experience consuming model endpoints over REST/gRPC, deploying asynchronous worker queues, and integrating serverless compute/microservices

Skills

Required

• Foundation models
• Context management
• Advanced proficiency in Python
• Advanced proficiency in TypeScript

Preferred

• Active Top Secret (TS) Clearance
• Deploying asynchronous worker queues