Synechron
Synechron
Synechron is a digital transformation consulting firm serving financial services and big tech organizations. Its work spans consulting, design, cloud, data, and engineering, with particular expertise in payments, sustainable finance, blockchain, and artificial intelligence. With a global team of more than 14,000 professionals, Synechron supports clients seeking to modernize technology, develop digital products, and respond to change across the financial services sector.

Lead AI Architect - Enterprise Generative AI and LLMs

Lead Synechron’s enterprise Generative AI, LLM, RAG and Agentic AI platforms. Shape Azure and AWS architecture, governance and large-scale AI delivery.

Description

  • Set and deliver Synechron’s AI and Generative AI roadmap against business objectives
  • Lead enterprise AI transformation and adoption initiatives
  • Work with business, product and executive stakeholders to identify AI opportunities and shape innovation strategies
  • Build, mentor and support multidisciplinary AI engineering, architecture and data science teams
  • Create AI governance, responsible AI, risk management and decision-making frameworks
  • Design enterprise-scale AI and Generative AI platforms and solutions
  • Define architectures spanning data ingestion, model orchestration, RAG pipelines, vector databases, AI agents, integrations, security, monitoring and observability
  • Guide architecture decisions for LLM applications built with Azure OpenAI, AWS Bedrock and other foundation-model ecosystems
  • Set AI platform standards, reusable frameworks, design patterns and enterprise practices
  • Design scalable multi-agent and Agentic AI systems
  • Oversee complex AI programs from initial concept through production deployment
  • Lead architecture reviews, technical governance, solution quality assessments and delivery-risk management
  • Partner with engineering, DevOps, MLOps and cloud teams to support successful deployments
  • Monitor program dependencies, milestones, risks, decisions and outcomes
  • Present AI strategy, architecture choices, technical risks and delivery progress to technical and non-technical audiences
  • Shape leadership-level architecture decisions through evidence-based recommendations
  • Coach architects, AI engineers and technical leads
  • Lead technical discussions, design reviews, governance forums and solution-approval sessions
  • Define and assess enterprise AI architectures through architecture, governance, quality, risk and program-planning reviews
  • Verify that production solutions meet scalability, performance, security and compliance standards

Requirements

  • 10+ years of experience in AI architecture, software engineering, machine learning, data platforms, cloud architecture or related technical fields
  • Demonstrated success designing and delivering enterprise-scale AI and Generative AI solutions
  • Deep knowledge of Generative AI, LLMs, NLP, Transformer architectures, prompt engineering and model evaluation
  • Hands-on experience with RAG, Agentic AI frameworks, LangChain, LangGraph, MCP, AI guardrails and multi-agent systems
  • Extensive Azure and/or AWS experience, including Azure OpenAI Services and AWS Bedrock
  • Experience with Kubernetes, Docker, API Management and microservices architecture
  • Knowledge of vector databases, knowledge graphs, semantic search, data engineering and enterprise integration patterns
  • Strong understanding of MLOps, model monitoring, observability, production AI operations and AI lifecycle management
  • Track record managing cross-functional teams and large-scale delivery programs
  • Experience influencing architecture decisions and engaging executive and business stakeholders
  • A bachelor’s or master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering or a related field is required or preferred depending on applicable experience
  • Equivalent experience in AI platform engineering, enterprise architecture, cloud transformation, machine learning engineering, data engineering or technical program delivery may also qualify
  • Certifications in Azure AI, AWS Machine Learning, cloud architecture, enterprise architecture or equivalent technologies are preferred
  • Training in Generative AI, AI governance, responsible AI, AI security, MLOps, cloud-native architecture and program delivery is preferred
  • Ongoing professional development in AI architecture, LLM ecosystems, Agentic AI, cloud platforms, enterprise integration, governance and emerging AI technologies is expected

Benefits

  • Flexible workplace arrangements
  • Mentoring opportunities
  • Internal mobility
  • Learning and development programs

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