Technical Lead
First seen by Alion on Oct 3, 2026.
AI/ML Tech Lead
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.
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.
- 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, Graph RAG, Re-ranking).
- AI Security & Guardrails : Deploy active safeguards against prompt injection, model jailbreaks, hallucination, and data leakage.
- 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.
- Observability : Monitor model drift, data distribution shifts, and edge-case execution in live enterprise production environments.
- 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 :
- 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.
Tech Stack :
- Languages : Python (FastAPI, PyDantic, Asyncio), TypeScript, Go, or Java.
- Agentic Frameworks & AI Stack : LangGraph, AutoGen, CrewAI, LangChain, LlamaIndex, PyTorch, Hugging Face, and major LLM Provider APIs.
- Vector Engines & Knowledge Graphs : Qdrant, Pinecone, Milvus, Weaviate, Neo4j, RDF/Ontologies.
- AI Security & Guardrails : Adversarial prompt testing, red teaming concepts, and guardrail implementation.
- MLOps & Infra : 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.
Skills
Python, LangChain, LangGraph, Knowledge Graph, PyTorch, Neo4j, Artificial Intelligence, Machine Learning, LLM, RAG