Home/Jobs/Senior Principal Engineer –

- AI Search &
- Retrieval

Senior Principal Engineer –
- AI Search &
- Retrieval

Autodesk

Pune / IND

15+ years

Today

$97.6K–100K/yr

Full-time

Onsite

Skills Required

LLM

RAG retrieval-augmented AI

Embeddings

Vector Database semantic retrieval hybrid retrieval

Information Retrieval vector search learning-to-rank neural ranking cross-encoders rerankers

AI-powered search

Machine Learning

Description

Autodesk is seeking a Senior Principal Engineer for AI-powered Search Infrastructure to lead the development of next-generation search platforms integrating AI and machine learning technologies.

Company: Autodesk

Role: Senior Principal Engineer for AI-powered Search Infrastructure

Experience

- 15+ years of experience designing complex software systems
- 5+ years of experience in a technical leadership role within a large and distributed organization
- Significant hands-on engineering experience in languages such as Java
- Experience with cloud platforms such as AWS

Qualification

- Bachelor’s degree in Computer Science or a related field or equivalent practical work experience

Responsibilities

- Lead software architecture and system design of scalable, distributed, data-intensive search and AI services
- Define technical architecture for AI-powered search including query understanding, orchestration, retrieval, ranking/reranking, and integration of LLMs and ML models
- Drive evolution of search architectures combining lexical, semantic, vector and hybrid retrieval approaches
- Partner with product teams, ML/AI engineers, and leadership to define strategic technical roadmap and translate into production systems




- Establish architectural patterns for deploying and operating LLMs and ML models within latency-sensitive, high-scale search infrastructure
- Define approaches for evaluating search and AI quality including relevance, retrieval and ranking effectiveness, latency, reliability and cost
- Demonstrate ownership and accountability and work closely with engineering teams to deliver consistently
- Align technical direction with business needs balancing near-term opportunities with long-term platform architecture
- Champion engineering, AI/ML and operational best practices across the team and broader organization
- Hire and mentor senior engineers and help build high-performing engineering teams

Additional Responsibilities

- Monitor and improve reliability of complex systems at scale
- Manage security and compliance challenges in cloud products and platforms
- Understand lifecycle of ML/LLM-powered production systems including model integration, inference, evaluation, observability, latency and cost considerations

Nice To Have

- Experience building query orchestration or query intelligence systems using multiple retrieval strategies, models or data sources
- Experience with learning-to-rank, neural ranking, cross-encoders, rerankers or LLM-based relevance models
- Experience designing retrieval-augmented generation (RAG)



or retrieval-augmented AI architectures
- Experience with search relevance evaluation including offline evaluation, human relevance judgments, experimentation/A-B testing and production quality metrics
- Understanding trade-offs between lexical retrieval, embedding-based retrieval, neural reranking and LLM-based approaches
- Experience optimizing AI/search architectures for latency, quality, throughput and inference cost at production scale
- Familiarity with up-to-date ML infrastructure and model serving architectures

More Skills Lucene, Elasticsearch, OpenSearch, Large Language Models (LLMs), Machine Learning models, Ranking and reranking approaches, Hybrid retrieval architectures, Cloud infrastructure platforms (AWS), Distributed systems, Multi-tenant SaaS architectures, API design, Microservices, Stream processing

Prepare for this role

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