Lead AI Engineer

Position: Lead AI Engineer (Search Modernization)
Location: Austin, TX (Onsite)
Duration: 12+ months contract
H1B ONLY
10+ yrs
Job Description:
Mandatory Skills:
Elastic Search, OpenSearch, Python, LLM, GenAI, Semantic Search, Re-Ranking, AWS, SEO(Search engine optimization)

We are looking for an AI Engineer to modernize and enhance our existing regex/keyword-based ElasticSearch system by integrating state-of-the-art semantic search, dense retrieval, and LLM-powered ranking techniques.
This role will drive the transformation of traditional search into an intelligent, context-aware, personalized, and high-precision search experience.
The ideal candidate has hands-on experience with ElasticSearch internals, information retrieval (IR), embedding-based search, BM25, re-ranking, LLM-based retrieval pipelines, and AWS cloud deployment

Required Skills & Qualifications:
5–10 years of experience in AI/ML, NLP, or IR systems, with hands-on search engineering.
Strong expertise in ElasticSearch/OpenSearch: analyzers, mappings, scoring, BM25, aggregations, vectors.
Experience with semantic search:
Embeddings (BERT, SBERT, Llama, GPT-based, Cohere)
Vector databases or ES vector fields
Approximate nearest neighbor (ANN) techniques
Working knowledge of LLM-based retrieval and RAG architectures.
Proficient in Python; familiarity with Java/Scala is a plus.
Hands-on AWS experience (OpenSearch, SageMaker, Lambda, ECS/EKS, EC2, S3, IAM).
Experience building and deploying APIs using FastAPI/Flask and containerizing with Docker.
Familiar with typical IR metrics and search evaluation frameworks

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