Lead GenAI Engineer

About Client

The client is a global consulting, technology, and digital firm specializing in the financial services industry. Established in 2001, the company provides innovative solutions to help clients navigate digital transformation, enhance operational efficiency, and achieve strategic objectives. With a focus on banking, capital markets, and insurance, it leverages cutting-edge technologies such as blockchain, artificial intelligence, and data science to deliver customized IT solutions and business consulting services.

The company's commitment to innovation, combined with its industry expertise, positions it as a leader in driving technological advancements and helping financial institutions stay competitive in a rapidly evolving market.

Rate Range

$80-$84/Hr

Job Description

• We are looking for a highly skilled and hands-on Lead 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
• ChromaDB
• 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.

About ApTask

ApTask is a leading global provider of workforce solutions and talent acquisition services, dedicated to shaping the future of work. As an African American-owned and Veteran-owned company, ApTask offers a comprehensive suite of services, including staffing and recruitment solutions, managed services, IT consulting, and project management. With a focus on excellence, collaboration, and innovation, ApTask provides unparalleled opportunities for professional growth and development. As a member of the ApTask team, you will have the chance to connect businesses with top-tier professionals, optimize workforce performance, and drive success across diverse industries. Join us at ApTask and be part of our mission to empower organizations to thrive while fostering a diverse and inclusive work environment.

Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.

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