10+ Years of experience • Full Time • India

Job Profile:

We are looking for a Principal Ai Engineer with 10+ years of experience to lead AI engineering strategy while remaining hands-on in building production-ready AI solutions. The role involves designing scalable AI architectures, developing LLM, RAG, and Agentic AI solutions, driving technical innovation, and mentoring AI engineers to deliver secure, reliable, and high-performance AI products.

Roles and Responsibilities

- Experience: 10+ years in software engineering, with 5+ years of strong hands-on experience in AI/ML and Generative AI.
- Act as the highest technical authority within the AI engineering function, providing technical direction to AI Leads, Senior AI Engineers, and AI Engineers.
- Remain highly hands-on in designing, developing, and deploying production-grade AI solutions.
- Define the overall AI technical architecture, engineering standards, development practices, and technology roadmap.
- Lead the design and implementation of solutions using LLMs, Generative AI, RAG, AI Agents, MCP, tool calling, function calling, and AI orchestration.
- Evaluate and select appropriate LLMs, AI frameworks, models, vector databases, infrastructure, and cloud services.
- Design scalable and secure architectures for AI products, SaaS platforms, and enterprise AI solutions.
- Lead complex and high-impact AI initiatives from POC MVP production.
- Establish best practices for prompt engineering, context management, memory, RAG pipelines, agent workflows, and AI evaluation.
- Drive the development of reusable AI frameworks, components, services, and engineering standards across projects.
- Establish approaches for LLM evaluation, hallucination detection, accuracy, latency, reliability,



and cost optimization.
- Guide the team in implementing AI observability, monitoring, testing, and production quality controls.
- Provide technical leadership for AI security, including prompt injection, data privacy, access control, and secure tool execution.
- Stay current with emerging AI technologies and assess their practical application within the organization.
- Conduct technical POCs and validate new AI technologies, models, and architectures.
- Mentor and technically guide the AI Team Lead, Senior AI Engineers, and AI Engineers.
- Conduct architecture reviews, technical reviews, and code reviews for critical AI solutions.
- Set technical direction while allowing AI Leads and Senior Engineers to independently manage day-to-day execution.
- Collaborate with Product, Engineering, DevOps, Security, and Business teams to translate business problems into scalable AI solutions.
- Define technical standards for AI development, documentation, testing, deployment, and maintenance.
- Optimize AI applications for performance, scalability, reliability, and infrastructure cost.
- Experience with Python and strong software engineering fundamentals is essential.
- Strong experience with APIs, microservices, databases, Docker, CI/CD, and cloud platforms.
- Experience with technologies/frameworks such as LangChain, LangGraph, LlamaIndex, OpenAI, Anthropic,



Gemini, Hugging Face, vLLM, or equivalent.
- Experience with vector databases/search technologies such as pgvector, Qdrant, Pinecone, Weaviate, Elasticsearch, or OpenSearch.
- Experience with AWS, Azure, or GCP and production AI deployments.
- Experience with open-source LLMs, model deployment, GPU infrastructure, or fine-tuning is an advantage.
- Strong understanding of AI/LLM security, responsible AI, and governance is preferred.
- Excellent technical communication, problem-solving, decision-making, and mentoring skills.
- Should be a hands-on technical leader, not a purely managerial or architectural role.

Key Skills

- Embedding Models & Vector Search
- AI Engineer
- python
- Natural Language Processing (NLP)
- TypeScript / JavaScript
- elasticsearch
- langchain
- MLOP
- LangGraph
- microservices architecture
- AI Agents & Multi-Agent Systems
- Fine-Tuning & Model Adaptation
- AI knowledge
- AI Safety & Guardrails
- PostgreSQL DBA
- Retrieval-Augmented Generation (RAG)
- Serverless Architectures
- Agentic AI
- Vector Databases
- Large Language Models (LLMs)

Office

India – Onsite

Information Security & Data Protection

- Adhere to the organizations and clients applicable information security, confidentiality, privacy, and data protection requirements.
- Safeguard company and client information and use it responsibly, ensuring protection against unauthorized access, disclosure, alteration, loss, or misuse.

Employee Benefits

Adaptable
Working Hours

Competitive
Base Salary

Medical
Insurance

Onsite Travel
Opportunities

Healthy
Luncheon

Trainings &
Certifications

Biannual
Company Trips

📌 Principal Ai Engineer (India)
🏢 BRIDGE Global
📍 India