Lead Architect

What you'll do

• Architect AI solutions and set technical direction for AI delivery practice
• Lead solution architecture for GenAI, Agentic AI, multimodal, and applied ML use cases
• Own reference architectures and solution design patterns for multimodal agentic systems
• Conduct solution design reviews and facilitate technical decisions
• Design and lead multi-agent systems with reasoning, planning, tool use, persistent memory, and grounded retrieval
• Guide multimodal system design across text, vision, speech, and structured data
• Establish patterns for SLM design and adoption to meet enterprise constraints
• Define hybrid retrieval and knowledge architectures spanning vector, graph, and NoSQL stores
• Establish evaluation frameworks, guardrails, and production quality standards
• Lead red-teaming and adversarial testing for high-stakes deployments
• Drive enterprise deployment best practices across cloud, on-prem, and edge
• Shape the practice's capability roadmap and mentor AI engineers
• Set technical hiring bar and lead architecture and senior engineering interviews
• Establish and promote AI in SDLC frameworks
• Partner with engineering, data science, product, and DX leadership on delivery initiatives
• Engage with client and stakeholder leadership on architecture, feasibility, and risk
• Support pre-sales and solutioning for new GenAI and Agentic AI opportunities

Requirements

• 10–12 years of hands-on experience building and deploying ML, DL, and AI systems in production
• Progression into solution architecture and technical leadership
• 10+ years experience working with global businesses on large accounts
• 3+ years hands-on work in GenAI and/or Agentic AI including multi-agent systems, custom fine-tuning, multimodal pipelines, or SLM-based deployments
• Proven track record architecting and shipping AI systems in enterprise-grade, regulated or high-stakes environments
• 3+ years experience leading ML-AI technical pods or teams, mentoring senior engineers, and setting hiring and review standards
• Advanced Python and SQL programming skills
• Strong API and backend engineering experience with FastAPI, Flask, or Django
• Experience with generative AI, agentic AI, eval & safety frameworks, machine learning and deep learning
• Experience with cloud platforms AWS, Azure, or GCP
• Experience with data engineering tools like Kafka, Spark, Flink, Hadoop, MongoDB
• Good to have experience with commerce cloud ecosystems such as Salesforce and Adobe
• Excellent communication skills
• Open and flexible toward hybrid work with minimum 3 days in office

Tech stack