AI Engineer – Tech Lead

3 - 5 years

11 - 22 Lacs

Posted:19 hours ago| Platform: GlassDoor logo

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Job Type

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Job Description

Job Title: AI Engineer – Tech Lead

Company: Skysecure Technologies
Location: Bangalore (Work From Office)
Profession: Information Technology
Discipline: Engineering Services

About Skysecure Technologies

Skysecure Technologies is a leading provider of cybersecurity, cloud, and AI-driven enterprise solutions, specializing in consulting, architecture, implementation, deployment, and managed services. We partner with organizations across industries to deliver secure, scalable, and intelligent systems powered by cutting-edge technologies from Microsoft, Palo Alto, CrowdStrike, and others. With a PAN-India presence and global client base, we are committed to enabling businesses to thrive in the era of digital transformation while maintaining security, innovation, and resilience at the core of every solution.

At Skysecure, you will work with enterprise clients, modern AI frameworks, and next-gen agentic systems, while being part of a collaborative, learning-driven, and innovative environment.

Role Overview

We are seeking a highly skilled AI Engineer – Tech Lead with a strong foundation in AI/ML technologies, intelligent agent frameworks, and cloud-native development. This role blends hands-on engineering with strategic leadership, guiding teams to build scalable, production-grade AI systems that solve complex real-world problems.

You will lead the design and development of agentic AI solutions leveraging Azure OpenAI, Semantic Kernel, and multi-agent architectures, while mentoring engineers and driving innovation across enterprise projects.

Key Responsibilities

1. AI Agent Development

  • Architect and develop scalable multi-agent systems using Azure AI Foundry Agent Service and Semantic Kernel SDK.
  • Build specialized agents (retrieval, planner, executor, evaluator) for end-to-end workflow orchestration.
  • Provide technical leadership for defining agent architectures, scalability, and performance strategies.

2. Retrieval-Augmented Generation (RAG)

  • Implement text and multimodal RAG pipelines with Azure AI Search, Cognitive Services, and Cosmos DB (Graph-RAG).
  • Optimize retrieval accuracy, grounding, and response relevance through experimentation.

3. Model Management & LLMOps

  • Fine-tune, evaluate, and deploy LLMs (Azure OpenAI GPT-4o, GPT-3.5, Llama-2, Mistral).
  • Manage model lifecycle using Prompt Flow, GitHub Actions, and CI/CD pipelines.
  • Define governance practices for prompt, model, and agent deployment.

4. API & Integration Engineering

  • Expose agent capabilities via REST and WebSocket APIs using FastAPI or Azure Functions.
  • Lead integration with Microsoft 365 (Graph API, Teams, Power Platform) and third-party SaaS.
  • Establish API security, authentication, and scalability standards.

5. Trust, Safety & Observability

  • Implement safety controls with Azure AI content filters, RBAC, and governance policies.
  • Oversee observability with Application Insights, telemetry dashboards, incident tracking, and RCA.

6. Collaboration & Mentoring

  • Mentor engineers in agentic patterns, Azure-native development, and architecture decisions.
  • Lead pair programming, code reviews, and internal workshops to drive team growth.
  • Partner with product and UX teams to deliver solutions in agile cycles.

7. No-Code and Low-Code AI Approaches

  • Leverage Power Automate, Power Virtual Agents, and Builder.io for rapid AI workflows.
  • Architect citizen developer workflows while ensuring backend integrity.
  • Enable cross-functional stakeholders in building low-code AI solutions.

8. Cross-Functional Leadership

  • Act as a bridge between technical teams and business leaders.
  • Translate complex AI concepts into clear business-friendly insights.
  • Balance hands-on contributions with team leadership and unblock project delivery.

9. Research & Upskilling

  • Stay at the forefront of LLMs, RAG, and multi-agent orchestration trends.
  • Lead PoCs, tool evaluations, and technology adoption initiatives.
  • Conduct internal training and capability-building programs.

Required Skills

  • Bachelor’s degree in Computer Science, IT, or related field.
  • 3–5 years of experience in AI/ML engineering, with at least 2 years in agentic AI patterns.
  • Proven leadership of AI projects or teams delivering enterprise solutions.
  • Strong Python (preferred) or TypeScript expertise with FastAPI/Azure Functions.
  • Deep knowledge of Azure OpenAI, AI Search, AI Foundry/Studio, Cosmos DB, Container Apps.
  • Hands-on with frameworks: LangChain, Semantic Kernel, AutoGen, LangGraph.
  • Experience in NLP, embeddings, RAG pipelines, and prompt engineering.
  • Integration expertise with Microsoft Graph API, REST APIs, and token-based authentication.
  • CI/CD using GitHub Actions or Azure DevOps.
  • Excellent communication skills for both technical and non-technical audiences.

Desired Skills

  • Experience with multi-modal RAG, graph-based retrieval, and function-calling patterns.
  • Deployment expertise with IaC, containerization, and microservices.
  • Familiarity with M365 Copilot Studio, Teams Toolkit v5, Adaptive Cards.
  • Experience with WebSockets/SignalR for real-time agent interactions.
  • Certifications: DP-100, AI-900, Azure AI Engineer Associate (preferred).

Why Join Skysecure Technologies?

  • Build next-gen AI agent solutions at enterprise scale.
  • Work with Azure OpenAI, Semantic Kernel, and advanced AI frameworks.
  • Join a culture of innovation, collaboration, and technical excellence.
  • Competitive salary, benefits, and career growth opportunities.
  • Opportunity to mentor, lead, and shape AI engineering practices in a fast-growing company.

Job Types: Full-time, Permanent

Pay: ₹1,112,494.36 - ₹2,260,056.83 per year

Application Question(s):

  • What is your notice period in days?

Experience:

  • AI/ML engineering, with agentic AI patterns: 3 years (Required)

Work Location: In person

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