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Enterprise AI Technical Lead

CareerNet Technologies Pvt Ltd

 

Bengaluru, Karnataka, India

Posted On: 15+ days ago
Experience: 10+ years
Availability: Onsite
Openings: 1
Category: GenAI Technical Lead
Tenure: No Preference/Any
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Description

Key Skills: Agentic AI, Integration, Generative AI, Python, Gemini, AI Platform Architect

Roles and Responsibilities:

Enterprise Platform Rollout & Enablement 

  • Own the architecture and rollout of the enterprise AI platform across the product organization. 
  • Build and operate cost-effective infrastructure: model garden setup, budget controls and cost monitoring, model tiering, and fallback open-source models. 
  • Stand up and harden platform foundations - identity federation/SSO, IAM, tenant isolation, security and compliance guardrails, and observability. 
  • Enable users to adopt off-the-shelf capabilities (e.g., NotebookLM, enterprise search, code assistants) and provide the training and ongoing support that drives real adoption. 
  • Design and deliver a self-service agent factory - patterns, templates, and in-IDE guardrails - so teams can build and maintain their own agents safely. 

Product Development Lifecycle Agents 

  • Lead the design and build of agent workflows across the PDLC: 
  • Ideation: requirement ideation and generation, design specification generation. 
  • Development: coding assistants, source-code management. 
  • Deployment: CI/CD, deployment, and monitoring. 
  • Partner directly with product, engineering, and other business teams to understand their requirements and help build out their use-cases - not just ship infrastructure but drive measurable productivity gains. 
  • Establish evaluation, quality, and monitoring practices for agent workflows from sandbox to production. 

Cross-Platform Interoperability 

  • Build agents that interoperate with agents on other enterprise AI platforms, including cross-platform contracts, schema/intent mapping, and cross-perimeter authentication. 
  • Represent the product organization technically when working with other business teams on cross-platform agent designs. 

Across All Tracks - Leadership & Hands-on 

  • Own the technical strategy, standards, patterns, and guardrails for agentic workflow development, RAG, security, and governance. 
  • Lead and mentor a team across cloud and enterprise AI tracks; raise the bar through code review, pairing, and design reviews. 
  • Steer external delivery partners - scope work, review deliverables, and hold them to quality and timeline. 
  • Stay hands-on: build reference agents, RAG pipelines, integrations, and MCP connectors, and debug the hardest pieces (including non-deterministic retrieval/generation behavior). 

Skills Required:

  • 10+ years of software engineering experience, with 4+ years in a technical lead or staff-level role. 
  • Strong, current hands-on coding ability - you still build and ship. Proficiency in Python (and comfort across at least one other modern language). 
  • Experience designing and operating production AI/ML or LLM-based systems: agents, RAG, prompt/eval pipelines, or similar. 
  • Deep familiarity with Google Vertex AI / Gemini and the surrounding services (IAM, networking, observability, cost management). 
  • Experience building developer-facing platforms or internal tooling, and driving adoption with training and support. 
  • Experience integrating systems via APIs and connectors; comfort with authentication and identity federation (OAuth, SSO, workload identity). 
  • A track record of leading technical initiatives across teams and influencing without authority. 
  • Strong communication skills - able to work directly with both engineers and non-technical business stakeholders. 

Preferred Qualifications: 

  • Hands-on with Gemini Enterprise, Vertex AI, NotebookLM, or comparable enterprise AI tooling. 
  • Experience building agentic systems and orchestration (agent development kits, A2A protocols, MCP, tool/function calling). 
  • Experience with LLM gateways and routing (e.g., LiteLLM), model cost optimization, and multi-model fallback strategies. 
  • Experience managing or working alongside systems integrators / delivery partners. 
  • Familiarity with the modern PDLC toolchain (Jira/Confluence, Figma, GitHub, CI/CD) and AI coding assistants. 
  • Experience with AI governance, guardrails, data privacy, and compliance in an enterprise setting. 

Education: Bachelor's Degree/ Master's Degree in related field

Education

Any Graduate

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