Technical Lead - AI/ML

Giggso; Chennai District; On-site; INR 3,500,000 - 5,500,000; Full time

Benefits offered by this job

Pioneer Enterprise AI

High ownership & impact

Culture of innovation

Job summary

Giggso is seeking an AI/LLM Engineering Tech Lead to bridge architectural vision with hands-on code execution. You will lead an agile pod building enterprise-grade Agentic Workflows, Knowledge Graphs, and AI Security Safeguards.

You will own technical direction, mentor the team, and collaborate with product and client teams to deliver secure, scalable AI platforms.

Qualifications

• 5+ years in core software engineering; 3+ years delivering AI/LLM-based products to production.
• Proven track record leading agile pods and mentoring developers.
• Master’s in Computer Science, Data Science, AI, or equivalent with shipped products or open-source work.

Responsibilities

• Lead an engineering pod of AI/ML engineers, full-stack developers, and DevOps to ship low-latency AI features.
• Translate blueprints into actionable specs, clean code, and sprint backlogs.
• Enforce engineering excellence via code reviews, CI/CD testing, and robust error handling.

Skills

Python

LLM orchestration

AI/ML engineering

Leadership

Education

Master’s in CS/DS/AI or equivalent

Tools

LangGraph

LangChain

PyTorch

Neo4j/RDF Ontologies

Job description

At Giggso, we bridge the gap between high-level AI strategy and code-level execution. We build context-aware, secure enterprise AI engineering solutions across core Business Operations (Sales, Support, RevOps) and AI Security Operations.

Moving far beyond basic RAG and static prompts, Giggso builds foundational Data & Knowledge Layers—turning raw unstructured data and enterprise ontologies into trustworthy, audit-ready AI agents. From multi-modal agentic architectures to proactive AI red teaming and security guardrails, Giggso ensures enterprise AI operates reliably at scale.

Role Overview

We are seeking a high-ownership, hands-on AI/LLM Engineering Tech Lead to drive the technical execution of our core AI platforms. In this role, you will bridge deep architectural vision with direct code-level execution. You will lead an agile engineering pod building enterprise-grade Agentic Workflows , Knowledge Graphs , and AI Security Safeguards .

If you are driven by passion and innovation, determined to bend the limits to build something truly transformative — this role is for you.

Key Responsibilities

• Lead an engineering pod (AI/ML Engineers, Full-Stack Developers, and DevOps) to ship low-latency, production-ready AI features.
• Translate high-level blueprints into actionable technical specifications, clean codebases, and sprint backlogs.
• Enforce engineering excellence through code reviews, automated CI/CD testing protocols, and robust error-handling standards.

Hands-On Agentic & Knowledge Systems Development

• Architect & Code: Build multi-modal LLM workflows and autonomous agentic systems using modern orchestration frameworks.
• Knowledge Layer Integration: Implement knowledge graphs, dynamic ontologies, and advanced vector retrieval strategies (Hybrid Search, GraphRAG, Re-ranking) that go beyond standard naive RAG.
• AI Security & Guardrails: Deploy active safeguards against prompt injection, model jailbreaks, hallucination, and data leakage using core AI Security principles.

Production MLOps, Eval & Performance

• LLM Ops: Build automated pipelines for continuous model evaluation (e.g., RAGAS, TruLens), dynamic prompt versioning, and latency tracking.
• Cost & Throughput Optimization: Optimize token consumption, context window management, caching, and model inference costs across multi-cloud deployments.
• Observability: Monitor model drift, data distribution shifts, and edge-case execution in live enterprise production environments.

Cross-Functional Execution

• Collaborate closely with Product Managers, Solution Architects, and client teams to resolve complex edge cases and accelerate feature delivery.
• Serve as a technical mentor, elevating team execution standards and unblocking complex algorithmic or system challenges daily.

Required Qualifications:

Education & Experience:

• Experience: 5+ years of core software engineering experience, including 3+ years specifically architecting and delivering AI/ML or LLM-based products into production.
• Leadership: Proven track record leading agile pods, conducting technical design reviews, and mentoring developers.
• Education: Master’s in Computer Science, Data Science, AI, or equivalent practical experience demonstrated through shipped products or open-source contributions and professional certifications.

Technical Stack Requirements:

• Languages & Core CS: Strong mastery of Python (FastAPI, PyDantic, Asyncio) with familiarity in TypeScript, Go, or Java.
• Agentic Frameworks & AI Stack: Hands-on experience with modern LLM orchestration tools (LangGraph, AutoGen, CrewAI, LangChain, LlamaIndex), PyTorch, Hugging Face, and major LLM Provider APIs.
• Vector Engines & Knowledge Graphs: Direct working experience with vector databases (Qdrant, Pinecone, Milvus, Weaviate) and Knowledge Graph technologies (Neo4j, RDF/Ontologies).
• AI Security & Guardrails: Familiarity with adversarial prompt testing, red teaming concepts, and guardrail implementation.
• MLOps & Infra: Practical experience with Docker, Kubernetes, GitHub Actions, MLflow, Weights & Biases, and serverless AI infrastructure on AWS/GCP/Azure.

Soft Skills:

• Strong technical articulation and communication skills to engage with technical stakeholders, understand requirements, and present engineering solutions cleanly.

Why Join Giggso?

• Pioneer Enterprise AI: Work on cutting-edge Knowledge Graph (GraphRAG) and Agentic tech stacks that solve real business problems.
• High Impact & Ownership: Own features end-to-end—from initial prototype to enterprise deployment.
• Culture of Innovation: Collaborate with a team building high-trust AI engineering frameworks and production security platforms.
• Competitive package and flexible work culture