Senior Technical Lead

Pune, Maharashtra

Job Summary

AI Architect - Associate

Exp: 8.0 to 12.0 Year |

Location: Pune

Must-have Skills : Python, Architectural Design, Agent, Artificial Intelligence, Full Stack (for AI Integration)

Secondary Skills : AWS, PLM (Teamcenter, BMIDE, ITK, C, C++)

Degree : B.Tech/B.E.

Branch : Scientific, Information Technology, Computers, Mechanical Engineering

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Requirements: AI Architect - Associate (8+ Years of Total Experience)• Proven Delivery: Lead the end-to-end lifecycle of complex AI projects, moving beyond prototypes to deliver robust, production-grade industrial solutions.

Advanced AI Orchestration: Architect sophisticated Agentic AI systems and advanced RAG pipelines, utilizing Knowledge Graphs for context-aware reasoning.

Model Optimization: Demonstrate deep expertise in Python and the fine-tuning of LLMs to tailor model performance for specific domain requirements.

Modern Full-Stack: Build high-performance, scalable backends using FastAPI and lead full-stack development to ensure seamless integration of AI features.

Technical Governance: Own the technical roadmap by delivering rigorous High-Level (HLD) and Low-Level Designs (LLD) that ensure system scalability.

Cloud Native: Design and deploy secure, resilient architectures on AWS, leveraging cloud-native services to support heavy AI workloads.

Domain Expertise: Apply your experience in PLM or Manufacturing to solve real-world industrial challenges at the intersection of digital and physical worlds.

Engineering Excellence: Drive best practices in CI/CD, code quality, and security, ensuring that AI solutions meet the highest enterprise standards.

Visionary Leadership: Act as a hands-on technical mentor, bridging the gap between cutting-edge AI research and practical, value-driven engineering.

Key Responsibilities

1. To be responsible for providing technical guidance to a team of developers, enhancing their technical capabilities and increasing productivity.

2. To conduct comprehensive code reviews, establish and oversee quality assurance processes, performance optimization , implementation of best practices and coding standards to ensure successful delivery of complex projects.

3. To ensure process compliance in the assigned module| and participate in technical discussions/review as a technical consultant for feasibility study (technical alternatives, best packages, supporting architecture best practices, technical risks, breakdown into components, estimations).

4. To collaborate with stakeholders to define project scope, objectives, deliverables and accordingly prepare and submit status reports for minimizing exposure & closure of escalations.

Skill Requirements

Must-have Skills : Python, Architectural Design, Agent, Artificial Intelligence, Full Stack (for AI Integration)

Secondary Skills : AWS, PLM (Teamcenter, BMIDE, ITK, C, C++)

Degree : B.Tech/B.E.

Branch : Scientific, Information Technology, Computers, Mechanical Engineering

________________________________________

Requirements: AI Architect - Associate (8+ Years of Total Experience)• Proven Delivery: Lead the end-to-end lifecycle of complex AI projects, moving beyond prototypes to deliver robust, production-grade industrial solutions.

Advanced AI Orchestration: Architect sophisticated Agentic AI systems and advanced RAG pipelines, utilizing Knowledge Graphs for context-aware reasoning.

Model Optimization: Demonstrate deep expertise in Python and the fine-tuning of LLMs to tailor model performance for specific domain requirements.

Modern Full-Stack: Build high-performance, scalable backends using FastAPI and lead full-stack development to ensure seamless integration of AI features.

Technical Governance: Own the technical roadmap by delivering rigorous High-Level (HLD) and Low-Level Designs (LLD) that ensure system scalability.

Cloud Native: Design and deploy secure, resilient architectures on AWS, leveraging cloud-native services to support heavy AI workloads.

Domain Expertise: Apply your experience in PLM or Manufacturing to solve real-world industrial challenges at the intersection of digital and physical worlds.

Engineering Excellence: Drive best practices in CI/CD, code quality, and security, ensuring that AI solutions meet the highest enterprise standards.

Visionary Leadership: Act as a hands-on technical mentor, bridging the gap between cutting-edge AI research and practical, value-driven engineering.

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