GenAI Lead: Architecting Production-Ready AI Solutions

Synechron, Inc._USA Company; New York (NY); On-site; USD 140,000 - 155,000; Full time

Benefits offered by this job

Competitive compensation and benefits

Work abroad opportunities

10 days of paid annual leave

Parental leave plans

Insurance plan including medical, etc.

Retirement savings plans

Udemy for Business access

Coaching opportunities

Job summary

Synechron is seeking a GenAI Lead to drive the design, development, and implementation of Generative AI solutions across the organization in New York, NY. You will define the technical strategy, guide engineering teams, and partner with business stakeholders to build secure, scalable, production-ready GenAI applications that deliver measurable value.

The role requires hands-on experience with LLMs, RAG, AI agents, prompt engineering, model fine-tuning, and governance.

Qualifications

• 12+ years in software engineering, data science, machine learning, or AI delivery.
• 2+ years designing and implementing Generative AI solutions.
• Experience with Large Language Models and foundation model platforms such as OpenAI, Azure OpenAI, Bedrock, Vertex AI, Anthropic, or open-source models.
• Proven experience deploying RAG-based applications and AI assistants.
• Strong Python programming skills.
• Experience with LangChain, PyTorch, TensorFlow, or similar libraries.
• Experience with vector databases such as Pinecone, FAISS, Weaviate, Milvus, Chroma, or Azure AI Search.
• Understanding APIs, microservices, cloud platforms, databases, and enterprise integration.
• Knowledge of MLOps, LLMOps, CI/CD, containerization, and deployment automation.
• Experience leading technical teams and enterprise AI initiatives.
• Strong communication and problem-solving skills.

Responsibilities

• Define and execute the organization’s Generative AI technical strategy and roadmap.
• Lead the architecture, design, development, and deployment of GenAI solutions.
• Build production-grade applications using large language models, foundation models, and AI services.
• Design and implement solutions using Retrieval-Augmented Generation (RAG) AI agents and agentic workflows.
• Prompt engineering and prompt orchestration.
• Fine-tuning and model adaptation.
• Embeddings and vector databases.
• Text generation, summarization, classification, extraction, and conversational AI.
• Evaluate and select appropriate models (commercial, open-source, cloud-based).
• Develop reusable frameworks, accelerators, APIs, and components for GenAI adoption.
• Lead integration of GenAI with enterprise apps, data platforms, and APIs.
• Establish standards for model evaluation, accuracy, reliability, performance, cost, security, and scalability.
• Implement observability, monitoring, feedback loops, and continuous improvement.
• Ensure responsible AI practices including privacy, security, fairness, explainability, governance, and regulatory compliance.
• Collaborate with data scientists, software engineers, cloud architects, product managers, cybersecurity teams, and business stakeholders.
• Translate requirements into practical AI use cases and solutions.
• Lead proofs of concept and production transition.
• Mentor engineering teams in GenAI architecture and deployment.
• Stay current with advancements in LLMs, multimodal AI, AI agents, tooling, and best practices.
• Present strategies, designs, prototypes, and business outcomes to leadership.
• Contribute to pre-sales activities and client engagements when required.

Skills

GenAI leadership

LLM platforms

Python

LangChain

Vector databases

APIs & microservices

MLOps

Team leadership

Stakeholder mgmt

Tools

OpenAI / Azure OpenAI

Bedrock / Vertex AI

Hugging Face

Job description

Synechron is seeking a GenAI Lead to drive the design, development, and implementation of Generative AI solutions across the organization in New York, NY. You will define the technical strategy, guide engineering teams, and partner with business stakeholders to build secure, scalable, production-ready GenAI applications that deliver measurable value.

The role requires hands-on experience with LLMs, RAG, AI agents, prompt engineering, model fine-tuning, and governance.