Gen AI Lead/Architect

About the role

We are At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 17,000+, and has 58 offices in 22 countries within key global markets. Our challenge: we are seeking a hands-on GenAI Lead / Architect to design, develop, and deploy enterprise-scale Generative AI solutions. The role focuses on Agentic AI, RAG architectures, LLM orchestration, workflow automation, and scalable AI platform engineering.

Responsibilities

• Lead the architecture, design, and implementation of enterprise GenAI platforms and applications.
• Design Agentic AI and multi-agent workflows using LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or Llama Index.
• Build and optimize RAG pipelines, vector search solutions, embedding workflows, and enterprise knowledge systems.
• Develop AI solutions for business process automation, knowledge management, intelligent document processing, conversational AI, decision support, and developer productivity.
• Build scalable APIs and microservices using Python, FastAPI, or Flask.
• Implement AI monitoring, observability, security, governance, guardrails, and responsible AI practices.
• Optimize prompts, context management, model performance, latency, reliability, and cost.
• Drive cloud deployment, CI/CD, DevOps, and MLOps practices.
• Collaborate with stakeholders to identify AI opportunities and translate business needs into scalable solutions.
• Mentor engineering teams and establish enterprise AI best practices.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related field, or equivalent practical experience.
• Strong expertise in Generative AI and LLMs, including OpenAI GPT, Claude, Gemini, Llama, or Mistral, with knowledge of prompt engineering, fine-tuning, function calling, tool integration, agent orchestration, context management, and memory handling.
• Proficiency in Python and experience building REST APIs, microservices, and enterprise integrations using FastAPI or Flask.
• Practical experience with RAG architecture, vector databases, embedding models, semantic and hybrid search, and document ingestion pipelines, using technologies such as Pinecone, Weaviate, ChromaDB, FAISS, Milvus, Elasticsearch, or OpenSearch.
• Knowledge of Docker, Kubernetes, CI/CD, GitHub Actions, Jenkins, GitLab CI, Terraform, and cloud platforms such as AWS, Azure, or GCP.
• Familiarity with MLOps, model deployment, monitoring, logging, AI governance, security, SQL/NoSQL databases, and data pipelines.
• Strong communication, problem-solving, and stakeholder management skills.
• Preferred, but