Gen AI Engineer (Typescript and Python)

AI Engineer: Typescript and Python, Gen AI, Agentic AI Experience Required: 6+ Years Role Overview: Design, develop, and deploy scalable AI/ML and GenAI solutions to solve complex business problems. Work closely with data scientists, business stakeholders, and cloud teams to build production-grade AI systems. Must Have Technical/Functional Skills 6+ years of experience building large‑scale distributed systems with strong expertise in LLM systems, agentic workflows, advanced ML infrastructure, async processing, queues, and streaming systems. Experience working with Typescript and Python in GenAI and agentic contexts. Advanced proficiency in Python, hands‑on experience with PyTorch, TensorFlow, and Hugging Face. Practical knowledge of model orchestration frameworks (e.g., LangChain, LlamaIndex, CrewAI) and familiarity with vector databases. Experience with cloud platforms (AWS, Azure AI, Google Cloud Vertex AI) and containerization technologies. Proven ownership of complex, cross‑cutting agentic systems spanning multiple teams or products. Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud infrastructure. Deep experience across the agentic AI stack, including planning, tool use, memory, and evaluation. Fluency with AI‑assisted and agentic development workflows. Ability to influence technical direction and align teams without formal authority. Problem‑solving skills, cross‑functional collaboration, and the ability to articulate complex AI concepts to non‑technical stakeholders. Drive technical direction for agentic AI initiatives, influencing architecture patterns, autonomy boundaries, and system design. Design, build, and operate production‑grade agentic AI systems used across multiple products. Own and evolve shared agentic AI capabilities, including design and development of agent frameworks and orchestration layers, planning, tool use, and memory strategies. Design retrieval and grounding (RAG) pipelines. Maintain LLM infrastructure, inference, and model gateway. Implement evaluation, observability, and safety tooling for autonomous systems. Lead technical design reviews and help teams navigate trade‑offs involving autonomy, safety, reliability, scalability, and cost. Partner across teams to deliver complex, cross‑cutting agentic AI initiatives from concept to product. Evaluate emerging models, techniques, and agentic patterns and translate them into practical, enterprise‑ready improvements. #J-18808-Ljbffr Stanley David and Associates