AI Lead Developer (GenAI & Agentic Solutions)

Role: AI Lead Developer (GenAI & Agentic Solutions)
Location: Herndon, VA / Grand Prairie, TX/Mobile, Alabama US — Hybrid (minimum 4 days/week onsite is must)
Duration: Contract

Job Description :

We are looking for a profile that combines strong technical skills with effective business communication.

Key expectations include:

• Clear prioritization
• Regular, structured status updates
• Clear ownership of actions
• Stakeholder Management
• The ability to present and explain technical topics in a way that is relatable to the business
• The ability to translate business requirements into AI solutions and project a clear AI vision across relevant use cases
• candidates having strong lead experience who will be handling a team

AI Lead Developer (GenAI & Agentic Solutions)

Role Title: AI Lead Developer (Generative AI / Agentic AI)

Seniority: Senior / Lead (hands-on technical lead)

Role Objective

Drive the design, development, and industrialization of Generative AI and Agentic AI solutions in a global, high-tech enterprise setting. This role owns the journey from PoC → MVP → production with enterprise-grade quality: security, scalability, reliability, observability, and governance. Candidate must be platform-agnostic; hands-on Google Cloud Platform experience is preferred. Familiarity with classical AI/ML for hybrid solutions is a strong advantage.

Key Responsibilities

Technical Leadership & Architecture

• Define solution architecture for GenAI/agentic capabilities (RAG, tool/function calling, orchestration, guardrails).
• Make design decisions balancing quality, latency, cost, and compliance; produce lightweight architecture artifacts and decision logs.

Hands-on Delivery (Prototype to Production)

• Build and deploy production-ready GenAI services/APIs (microservices) and reusable components (accelerators, templates, SDKs).
• Implement data ingestion + retrieval pipelines (chunking, embeddings, indexing) and integrate enterprise data sources.
• Establish evaluation approach (benchmarks, regression tests, golden datasets) and manage prompt/model versioning.

LLMOps / Platform Enablement

• Implement CI/CD, automated testing gates, rollout strategies, monitoring/logging/tracing, and operational runbooks.
• Support incident/change workflows and ensure production readiness (SLOs, resiliency, cost controls).

Security, Privacy & Responsible AI

• Implement controls for PII protection, access management, auditability, prompt-injection mitigation, safety filters, and governance alignment.

Collaboration & Mentoring

• Partner with product, architecture, data, and security stakeholders; translate requirements into backlog and deliverables.
• Mentor engineers and align distributed/global teams on standards and delivery practices.

Required Skills & Experience

• 8+ years software engineering; 2+ years delivering GenAI/LLM solutions (hands-on).
• Demonstrated success taking at least one GenAI solution into production (not only PoCs).
• Strong coding in Python (and/or Java/Go/TypeScript) plus API/service engineering.
• Strong GenAI fundamentals: RAG, embeddings, prompt lifecycle, tool/function calling, agentic patterns, evaluation methods.
• Cloud-native engineering: containers, Kubernetes (or equivalent), CI/CD, IaC, observability.

Preferred / Nice to Have

• Hands-on GCP (e.g., Vertex AI, BigQuery, Cloud Run/GKE, Pub/Sub, IAM/Secret Manager).
• Classical AI/ML exposure for hybrid systems (prediction + GenAI).
• Experience with vector DB / enterprise search and working in regulated/high-security environments.

Deliverables

• Production-grade GenAI/agentic service(s) with monitoring, alerting, runbooks, and support readiness.
• Reference architecture + reusable components and quality gates (evaluation, security, performance, cost).

Secure integration with enterprise data and identity/access controls.