Senior Technical Specialist

Vibehackers; India; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Vibehackers seeks a Senior Technical Specialist to design and lead enterprise-scale GenAI and Agentic AI solutions. You will architect reference architectures, governance, and multi-agent workflows while balancing innovation, risk, and business value.

You will drive AI-first engineering, Vibe Coding practices, and secure adoption across platforms like Vertex AI or Azure AI Foundry, ensuring scalable, compliant, and observable systems.

Qualifications

• Proven experience designing enterprise GenAI/Agentic AI solutions.
• Hands-on knowledge of prompt engineering, embeddings, and RAG.
• Experience with cloud AI platforms (Vertex AI, Azure OpenAI) is a plus.

Responsibilities

• Design end-to-end GenAI/Agentic AI solutions aligned to enterprise goals.
• Define scalable AI reference architectures and deployment strategies.
• Lead architecture reviews and drive AI platform decisions.
• Promote AI-first engineering and AI-assisted development practices.

Skills

AI Architecture

LLM Engineering

Prompt Engineering

AI Governance

Risk Management

Knowledge Management

AI Orchestration

Platform Engineering

DevOps CI/CD

Cloud Architecture

Technical Leadership

Security & Compliance

Job description

Explicitly requires Vibe Coding and AI-assisted development practices, including automated code generation and agent-assisted testing.

About the Role

Senior Technical Specialist to design and lead enterprise-scale AI solutions focused on Generative AI and Agentic AI, architecting platforms, governance, and LLM-based systems. The role leads AI orchestration, RAG/knowledge architectures, platform engineering (Vertex AI or Azure AI Foundry), and drives adoption of AI-assisted development and Vibe Coding practices.

Job Description

Role

Senior Technical Specialist / AI Solution Architect responsible for designing, leading, and governing enterprise-scale Generative AI and Agentic AI solutions. The role focuses on architecting scalable AI reference architectures, building multi-agent workflows, defining AI governance controls, and enabling secure enterprise adoption while balancing innovation, risk, compliance, and business value.

Key Responsibilities

• Design end-to-end GenAI and Agentic AI solutions aligned to enterprise objectives.
• Define scalable AI reference architectures, integration patterns, and deployment strategies.
• Lead architecture reviews and technology decisions for AI platforms and toolchains.
• Drive enterprise adoption of AI-first engineering and AI-assisted development practices.

Agentic AI & Orchestration

• Architect multi-agent and agentic workflows using LangGraph.
• Design deterministic and non-deterministic orchestration strategies, including workflow routing, tool calling, memory management, and reasoning chains.
• Define human-in-the-loop approval and exception handling mechanisms.
• Design Retrieval Augmented Generation (RAG) solutions and govern knowledge/context stores, vector databases, and semantic search frameworks.
• Define prompt engineering standards, prompt lifecycle management, and evaluation frameworks.
• Optimize systems for accuracy, latency, cost, and explainability.
• Architect solutions using Google Vertex AI or Azure AI Foundry.
• Design platform capabilities such as model hosting, prompt management, model gateway, observability, safety guardrails, and LLMOps practices.

Vibe Coding Leadership

• Drive adoption of AI-assisted development and Vibe Coding practices including automated code generation, agent-assisted testing, and AI code review.
• Establish governance and quality controls for AI-generated code and measure development productivity.
• Define Responsible AI frameworks and governance controls, conduct AI risk assessments and model risk reviews.
• Implement controls for data privacy, security, compliance, hallucination mitigation, prompt injection protection, model monitoring, and human oversight.

Requirements

• Proven experience in AI architecture and designing enterprise GenAI/Agentic AI solutions.
• Hands-on knowledge of LLM engineering topics: prompt engineering, prompt optimization, model evaluation, RAG, embeddings, and vector search.
• Familiarity with agentic frameworks (LangGraph, LangSmith, LangChain, Semantic Kernel preferred).
• Experience with cloud AI platforms (Google Vertex AI, Azure AI Foundry) and Azure OpenAI/Gemini/OpenAI ecosystems.
• Strong platform and engineering skills: Python, APIs & microservices, Kubernetes, Docker, CI/CD, GitHub/Azure DevOps, and LLMOps practices.
• Demonstrated experience defining AI governance, responsible AI, risk management, and regulatory compliance controls.
• Leadership capability to drive enterprise adoption and govern AI-assisted development practices.

Skills

AI Architecture Solution Architecture LLM Engineering Prompt Engineering AI Governance Risk Management Knowledge Management AI Orchestration Platform Engineering DevOps / CI/CD Cloud Architecture Technical Leadership Security & Compliance