InfoVision Inc.
Website:
infovision.com
Job details:
About the Role
We are looking for a seasoned AI Evangelist with 8–12 years of overall technology experience, including significant hands-on depth in Generative AI, LLMs, agentic systems, and the emerging MCP/tooling ecosystem. You have moved beyond experimentation — you've shipped GenAI systems in production, influenced technology direction at an organizational level, and can speak credibly to both engineers and CxOs. This role sits at the intersection of deep technical execution and external-facing influence.
Responsibilities
- GenAI Engineering
- Design and deliver production-grade GenAI solutions using LLMs (OpenAI, Gemini, Anthropic, Mistral, open-source), RAG pipelines, and agentic frameworks.
- Build and lead multi-agent systems using LangChain, LangGraph, and custom orchestration layers.
- Architect and implement MCP (Model Context Protocol) servers and tool-use / function-calling patterns for agentic workflows.
- Evaluate, benchmark, and recommend LLM models for specific enterprise use cases at scale.
- Drive adoption of responsible AI practices — guardrails, observability, hallucination mitigation.
- Evangelism & Thought Leadership
- Represent the organization at conferences, webinars, and client workshops as a senior AI subject matter expert.
- Develop reference architectures, whitepapers, demos, and proof-of-concepts showcasing GenAI capabilities.
- Drive internal AI adoption through enablement programmer, hackathons, and CoE leadership.
- Mentor mid-level engineers on GenAI patterns, prompt engineering, and agentic design.
- Client & Stakeholder Engagement
- Engage with CxO, VP, and architect-level stakeholders to assess AI readiness and co-create GenAI transformation roadmaps.
- Lead discovery workshops, solutioning sessions, and pre-sales technical discussions.
- Translate complex AI concepts into tangible business outcomes for non-technical audiences.
- Full Stack & Cloud Delivery
- Develop and deploy AI-powered applications using React / Angular (frontend), Node.js / Python (backend).
- Deploy and manage AI workloads on AWS (Bedrock, SageMaker, Lambda, ECS, etc.).
- Apply DevOps best practices — CI/CD, containerization, IaC — to AI delivery pipelines.
Qualifications
- Overall Experience
- 8–12 years of total software / technology experience.
- At least 3–5 years of dedicated, hands-on Generative AI / LLM engineering experience.
- Prior experience in a client-facing, consultative, or evangelism-adjacent role preferred.
Locations: Pune, Bangalore, Hyderabad, Chennai.
Required Skills
- Must-Have — GenAI & AI Engineering
- Deep expertise in LangChain and LangGraph for agentic and RAG workflows.
- Production experience with OpenAI APIs (GPT-4o, o1, Assistants API) and Google Gemini models.
- Experience building or consuming MCP servers and tool-calling / function-calling patterns.
- Strong command of RAG architectures — chunking, vector stores (Pinecone, Weaviate, pgvector, OpenSearch), reranking, hybrid search.
- Broad LLM familiarity: open-source models (LLaMA, Mistral, Phi), fine-tuning approaches, and model evaluation frameworks.
- Strong-to-Have — Full Stack
- Strong Python for AI/ML backend development and pipeline orchestration.
- Proficiency in Node.js and at least one frontend framework (React or Angular).
- REST / GraphQL API design, microservices, and system integration patterns.
- Strong-to-Have — Cloud & DevOps
- Hands-on AWS experience — Bedrock, SageMaker, Lambda, S3, RDS, ECS/EKS.
- Docker, Kubernetes, CI/CD pipelines, and infrastructure-as-code (Terraform / CDK).
- Experience with prompt engineering at scale, fine-tuning, or RLHF workflows.
- Exposure to multimodal AI — vision, voice, document intelligence.
- Contributions to open-source AI projects, published blogs, or conference talks.
- Certifications: AWS Solutions Architect / ML Specialty, Google Cloud Professional AI Engineer.
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