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Lead GenAI Engineer

• Banking Client Exp required
• In Person Interview at Vallum Associates Lead GenAI Engineer
• Banking Client Exp required
• In Person Interview at Vallum Associates in Woodside, New York Posted in about 12 hours ago.

Type:

full-time

Job Title:

Lead GenAI Engineer

• Banking Client Exp required

Location:

Manhattan, NY (3 days a week onsite)

Duration:

6 months rolling contract £70/Hr on C2C GC and USC Candidates only Interview Process

• 2 Rounds
• Interview will be in person in NY office Description We are looking for a highly skilled and hands-on GenAI Engineer to drive the design, development, and deployment of enterprise-scale Generative AI solutions.

The ideal candidate will have strong expertise in Agentic AI workflows, RAG architectures, LLM orchestration, workflow automation, and scalable AI platform engineering . This role requires both technical depth and the ability to translate complex business problems into practical AI-driven solutions. Key Responsibilities Lead the architecture, design, and implementation of enterprise GenAI platforms and AI-powered applications. Design and develop Agentic AI workflows using autonomous and multi-agent frameworks. Build and optimize RAG (Retrieval-Augmented Generation) pipelines integrating enterprise knowledge sources. Develop intelligent workflow automation solutions using GenAI and AI agents. Collaborate with business stakeholders to identify AI opportunities, define use cases, and architect scalable solutions.

Create AI solutions for:

Business process automation Knowledge management Intelligent document processing Conversational AI Decision support systems Code generation and developer productivity Design scalable APIs and microservices for AI applications. Implement observability, monitoring, guardrails, security, and governance for AI systems. Optimize LLM performance, prompt engineering, latency, and cost efficiency. Mentor engineering teams and establish AI engineering best practices. Drive deployment automation and production readiness using DevOps and MLOps practices. Required Skills & Experience Generative AI & LLMs Strong experience with: OpenAI GPT models Claude Gemini Llama Mistral Expertise in: Prompt engineering Fine-tuning concepts Function calling / tool usage AI agent orchestration Context management Memory handling Agentic AI & Workflow Orchestration Experience designing autonomous AI systems using: LangChain LangGraph CrewAI AutoGen Semantic Kernel LlamaIndex Strong understanding of: Multi-agent systems Planning and reasoning workflows Human-in-the-loop workflows AI orchestration patterns RAG & Knowledge Systems Hands-on experience with: RAG architecture design Vector databases Embedding models Semantic search Hybrid search Chunking strategies Document ingestion pipelines Experience with vector databases such as: Pinecone Weaviate Chroma

DB FAISS

Milvus Elasticsearch/OpenSearch vector search Backend & API Development Strong Python development experience.

Experience building:

REST APIs FastAPI / Flask services AI microservices Async processing pipelines Familiarity with API integration patterns and enterprise integrations. Cloud, DevOps & Deployment Experience with: Docker Kubernetes Containerization CI/CD pipelines GitHub Actions / Jenkins / GitLab CI Terraform or Infrastructure as Code Cloud platform expertise in one or more: AWS Azure GCP Exposure to: MLOps Model deployment Monitoring and logging AI governance and security Frontend & UI Working knowledge of: Angular TypeScript React (good to have) Ability to collaborate on AI-powered UI/UX workflows and conversational interfaces. Data & Databases Experience with: SQL / NoSQL databases PostgreSQL MongoDB Redis Data pipelines ETL workflows Good to Have Experience with AI copilots and enterprise assistants. Knowledge of MCP (Model Context Protocol).

Experience with workflow tools like:

Apache Airflow n8n Temporal Camunda Exposure to AI security, responsible AI, and governance frameworks. Experience in Capital Markets, Banking, Healthcare, Retail, or other enterprise domains. Familiarity with OCR, speech-to-text, and multimodal AI solutions. Qualifications Bachelor's or Master's degree in Computer Science, Engineering, AI, or related field. 8+ years of software engineering experience with 3+ years in AI/GenAI architecture and solutioning. Strong communication and stakeholder management skills. Proven ability to lead technical teams and drive enterprise AI adoption. Preferred Profile Strong problem solver who can convert ambiguous business challenges into scalable AI solutions. Ability to balance innovation with enterprise-grade architecture and operational excellence. Passion for emerging AI technologies and rapid experimentation.