AI Technical Lead

Generac International; Pune District; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Generac seeks a senior AI Solutions Delivery leader to own end-to-end delivery of AI initiatives, from design handoff to production deployment, in partnership with PMs and AI architects. You will translate designs into actionable plans, track progress, and ensure readiness across IAM, cross-cloud integrations, and security controls.

Daily collaboration with engineers to align designs, review code, and remove blockers, while driving adherence to architecture and deployment gates for

Responsibilities

• Own end-to-end delivery of AI solutions from design handoff through production deployment.
• Translate solution designs into sequenced, actionable engineering plans.
• Track delivery progress, identify risks, and keep solutions on track.
• Define and enforce production readiness criteria and deployment gates.
• Coordinate across engineering, data, platform, and QA to resolve blockers.

Skills

IAM

Cross-cloud integrations

MLOps

CI/CD

Observability

Job description

We are Generac, a leading energy technology company committed to powering a smarter world. Over the 60 plus years of Generac's history, we've been dedicated to energy innovation. From creating the home standby generator market category, to our current evolution into an energy technology solutions company, we continue to push new boundaries.

Driving Solution Delivery in partnership with Program Managers & AI Principal Architects

• Own end-to-end delivery of AI solutions from design handoff through production deployment, keeping momentum and quality high throughout. Works in partnership with Program Managers to deliver on roadmap timelines that falls within a PI or across multiple PIs.
• Translate solution designs received from Principal AI Solution Architects into sequenced, actionable engineering plans the team can execute immediately
• Track delivery progress across workstreams, identify risks early, and intervene proactively to keep solutions on track. Reports progress to program managers to keep delivery on track. Supports Program Managers in sizing & sequencing of the work and identifying dependencies.
• Make day-to-day implementation decisions within the scope of the agreed architecture, escalating only those decisions that could alter the solution's design or scope
• Coordinate across engineering, data, platform, and QA teams to resolve cross-functional dependencies and remove delivery blockers
• Define and enforce 'done': production readiness criteria, acceptance conditions, and deployment gates for each solution component
• Strong understanding of authentication, authorization, and Identity & Access Management (IAM) concepts, including role-based access controls, service identities, and enterprise security integration.
• Experience designing and implementing solutions that leverage cross-cloud integrations, secure network communications, APIs, and connectivity across cloud and enterprise platforms.
• Working knowledge of cloud governance, security frameworks, compliance controls, and operational best practices for enterprise-scale AI and data platforms.
• Experience implementing security controls for AI/ML applications, data protection, secret management, and secure access to enterprise systems.
• Familiarity with observability and monitoring frameworks, including logging, metrics, tracing, alerting, and platform performance monitoring to ensure reliability and operational excellence.

Working Directly With Engineers

• Work alongside engineers daily -- pairing on hard problems, reviewing designs before they become code, and reviewing code before it ships
• Provide engineers with the technical context, design rationale, and decision support they need to move fast without guessing
• Translate high-level solution architecture into component-level and interface-level designs that engineers can implement directly
• Identify when an engineer is stuck, heading in the wrong direction, or about to make a costly mistake -- and step in immediately
• Break down complex solution components into well-scoped tasks that individual engineers can pick up and complete with confidence
• Run focused technical working sessions (design reviews, implementation walkthroughs, debugging sessions) to keep the team aligned and unblocked
• Serve as the primary technical escalation point for engineers before issues are raised to Principal Architects or program managers

Hands-On Engineering Contribution

• Write production-quality code for the most complex, highest-risk, or most technically ambiguous parts of each solution
• Build shared utilities, integration layers, and implementation patterns that accelerate the broader engineering team
• Perform deep code reviews with a focus on correctness, maintainability, performance, and alignment with the solution design
• Lead debugging and root-cause analysis for complex issues across ML pipelines, APIs, and data systems
• Validate solution components through testing, profiling, and hands-on verification before sign-off

Technical Quality & Production Readiness

• Own the quality bar for every solution delivered -- ensuring components are tested, observable, documented, and ready for production operation
• Establish and enforce testing standards: unit, integration, and end-to-end coverage for AI/ML pipelines and APIs
• Implement MLOps practices for each solution: experiment tracking, model versioning, CI/CD pipelines, monitoring hooks, and alerting
• Ensure operational runbooks, deployment guides, and post-deployment support documentation are produced as part of every delivery

Communication & Stakeholder Alignment