Request ID: 107145-1
Title: Lead Generative AI Engineer
Location: Dallas, TX / Hybrid
Duration: 6 months
Pay Range: $50 - $56/Hour on W2/C2C (All inclusive)
Skills: Python, Machine Learning, Artificial Intelligence(AI)~Generative AI
Experience Required: 6 - 10 years relevant experience
Summary
Build and scale a production multi-agent AI platform serving thousands of internal users across multiple business units. Monthly release cadence, real users, real latency, real cost.
Must Have:
•Strong hands-on experience in building Agentic AI solutions and frameworks. The evaluation should focus on this.
•Associates should demonstrate their experience designing and implementing Agentic AI solutions in real-world environments.
•A self-driven mindset with the ability to work independently and take ownership.
•Experience working on large-scale initiatives for major enterprise clients.
•Clear articulation of their use cases, specific contributions and impact within project teams.
•Ability to confidently explain solution scenarios, architecture decisions, challenges, and outcomes.
•Confidence and capability to design and develop their own AI use cases from concept to execution.
Responsibilities
• LLM-driven orchestrator that routes user intent across a portfolio of specialized agents — delegation, memory, response validation, capability discovery.
• Agent selection layer — hybrid retrieval (vector RAG over a capability registry) plus closed-set LLM selection with JSON-schema-constrained outputs.
• Multi-agent SDK / gateway — FastAPI service hosting many agents behind path-prefix routing, per-agent tool registries, session-scoped conversational context.
• Tool-driven agents — 15–30 tools per agent composed dynamically by an LLM; owns tool contracts, guardrails, and evaluation.
• Data API layer — parameterized endpoints between agents and databases; LLMs never touch DBs directly.
• Partner-team onboarding — versioned A2A contract, bring-your-own-agent registration, auto re-embedding.
Core AI Engineering
• Production LLM systems: RAG, tool/function-calling loops, structured outputs, hallucination guards, closed-set selection.
• Multi-agent orchestration: A2A protocols, session affinity, human-in-the-loop gating, kill switches, graceful degradation.
• Vector search + embeddings at scale (sub-second retrieval over thousands of docs).
• Evaluation & safety: PII/PHI masking, audit trails, feedback-loop instrumentation, offline + online eval.
Platform / Infrastructure
• Python 3.11+, FastAPI, async I/O, Pydantic.
• Modern LLM stacks (Gemini, GPT, Claude) and agent frameworks (LangGraph, Agent SDKs).
• Cloud (GCP or AWS): Kubernetes, object storage, workflow orchestration, Vertex/Bedrock-class services.
• Redis, MongoDB, Oracle/Postgres, SSO + RBAC.
• Observability: Prometheus, structured JSON logs, per-decision audit trails, p95 latency SLOs in seconds.
Company Benefits & Culture
• Inclusive and diverse work environment
• Opportunities for professional growth and development
• Comprehensive health and wellness benefits