Principal Engineer - Agentic AI Architect

Job Title

Principal Engineer - Agentic AI Architect

Role Summary

Lead the architecture and development of agentic AI systems that integrate large language models, multi-agent orchestration, and RAG pipelines with FPGA/ASIC platforms. Drive technical strategy, define end-to-end system architecture, and coordinate cross-functional teams to deliver hardware-aware AI solutions.

Experience Level

Senior-level role. The position expects approximately 10+ years of relevant experience in AI/ML systems, distributed systems, or hardware–software co-design.

Responsibilities

Design, build, and lead deployment of production agentic AI systems that combine software intelligence with hardware acceleration.

• Define end-to-end AI system architecture: data ingestion → reasoning → action.
• Design and implement agentic AI using LLMs, tool-using agents, planning/reasoning agents, and multi-agent orchestration.
• Architect and implement RAG pipelines and enterprise knowledge integration with vector databases.
• Co-design AI workflows with FPGA/ASIC acceleration and heterogeneous compute (CPU/GPU/FPGA).
• Optimize LLM inference on FPGA: quantization, compilation, partitioning and performance tuning.
• Build internal platforms and reusable components (memory, tool integration, agent orchestration) using frameworks such as LangChain and LlamaIndex.
• Lead architecture reviews, mentor engineers, and influence cross-functional engineering and hardware teams.

Requirements

Core technical qualifications and hands-on skills required for the role.

• Experience: ~10+ years leading AI/ML systems, distributed systems, or hardware–software co-design.
• AI/LLMs: Recognized expertise with large language models, LLM architectures, inference, prompt engineering, memory and reasoning optimization.
• Agentic AI / RAG: Deep experience with agent frameworks, multi-agent orchestration, and retrieval-augmented generation workflows.
• Production systems: Hands-on history building production-grade LLM applications, multi-step reasoning workflows, and scalable, reliable deployments.
• Hardware integration: Strong background with FPGA, ASIC, EDA systems and heterogeneous compute architectures; experience collaborating with hardware teams.
• Programming & systems: Proficient in Python; C++ preferred. Experience with distributed systems design, APIs, microservices, and cloud/edge deployment.
• Model optimization: Practical experience with LLM fine-tuning, quantization, distillation, and inference optimization for constrained hardware.
• Nice-to-have: Familiarity with compiler stacks (MLIR, TVM), robotics/real-time pipelines, LangChain/LlamaIndex, on-device edge deployment, and tool integration frameworks.

Education Requirements

Master's or Bachelor's degree (stated in posting) in a technical field such as Computer Science, Electrical/Computer Engineering, or related engineering discipline; posting pairs the degree expectation with approximately 10+ years of experience in AI/ML systems, distributed systems, or hardware–software co-design.

About the Company

Company: Altera

Headquarters: Bengaluru, Karnataka, India

Altera provides leadership programmable solutions for applications ranging from cloud to edge, unveiling limitless AI possibilities. Their extensive product portfolio includes FPGAs, CPLDs, Intellectual Property, development tools, and System on Modules aimed at accelerating innovation in various fields.