Enterprise Search Tech Lead

Enterprise Search Tech Lead

Responsibilities

Leading design, development, and optimization of enterprise search solutions built on AWS OpenSearch to improve relevance, scalability, and AI-readiness across digital platforms.

Owning technical decisions across the full search stack: ingestion pipelines (Spring Boot/Batch, Kafka), search APIs, index design, and infrastructure-as-code.

Driving platform evolution toward hybrid retrieval (lexical + semantic/vector search) to support RAG, LLM grounding, and agentic AI use cases.

Creating and maintaining comprehensive technical documentation including C4 architecture models, system design diagrams, and operational runbooks.

Mentoring and leading developers on the search engineering team, conducting code reviews, and raising engineering standards.

Partnering with the domain architect on long-term strategy while independently executing complex platform changes.

Building and maintaining Airflow-orchestrated ingestion workflows, monitoring/alerting systems, and CI/CD pipelines.

Supporting cross-functional teams by troubleshooting search issues, monitoring system health, and partnering with consuming applications (product navigator, digital commerce, AI assistants).

Willingness to be on‑call in the event of critical issues requiring timely resolution.

Qualifications

Bachelor’s degree or higher in computer science, information systems, or technology field (completed and verified prior to start).

Five years of search‑related development experience in a private, public, government, or military environment.

Seven years of overall software engineering experience in a private, public, government or military environment.

Preferred Qualifications

Experience with AWS OpenSearch/Elasticsearch: index design, analyzers/tokenizers, synonyms, aggregations, relevance tuning, and performance optimization.

Experience with Java 17+, Spring Boot, Spring Batch, and multi‑module Maven projects.

Experience with Kafka/MSK messaging — producers, consumers, and stream processing.

Experience with AWS services (S3, IAM, Lambda, MSK, ECS, CloudWatch, EFS).

Strong understanding of search fundamentals (BM25, relevance tuning, autocomplete, vector search).

Experience with embeddings, vector databases, or RAG pipelines for LLM applications.

Experience building and operating Airflow DAGs for data pipeline orchestration.

Experience modernizing legacy search platforms or migrating between search engine versions.

Familiarity with search analytics, A/B testing for ranking, and relevance measurement (NDCG, MRR).

Demonstrated ability to document complex systems — C4 model, architecture decision records, or equivalent.

Work Location
Maplewood, MN or Austin, Texas

Travel
May include up to 10% domestic/international.

Relocation
May be authorized.

Legal Authorization
Must be legally authorized to work in country of employment without sponsorship for employment visa status (e.g., H1B status).

Compensation & Benefits
The expected compensation range for this position is $145,676 – $178,049, which includes base pay plus variable incentive pay, if eligible. This range represents a good faith estimate for this position. The specific compensation offered to a candidate may vary based on factors including, but not limited to, the candidate’s relevant knowledge, training, skills, work location, and/or experience.

Benefits may include: Medical, Dental & Vision, Health Savings Accounts, Health Care & Dependent Care Flexible Spending Accounts, Disability Benefits, Life Insurance, Voluntary Benefits, Paid Absences and Retirement Benefits, etc.

3M does not discriminate in hiring or employment on the basis of race, color, sex, national origin, religion, age, disability, veteran status, or any other characteristic protected by applicable law.

Responsibilities of this position include compliance with corporate policies, procedures and security standards while performing assigned duties.

Safety is a core value at 3M. All employees are expected to contribute to a strong Environmental Health and Safety (EHS) culture by following safety policies, identifying hazards, and engaging in continuous improvement.

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