Search Engineer​/Tech Lead

DivIHN (pronounced “divine”) is a CMMI ML3-certified Technology and Talent solutions firm. Driven by a unique Purpose, Culture, and Value Delivery Model, we enable meaningful connections between talented professionals and forward-thinking organizations. Since our formation in 2002, organizations across commercial and public sectors have been trusting us to help build their teams with exceptional temporary and permanent talent. Visit us at  to learn more and view our open positions.

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Title:

Search Engineer/Tech Lead

Location:

Charlotte, NC Duration: 6 Months

Note:

** Would like local, but can be remote. MUST BE EAST COAST TIME ZONE.
** Strong preference for Lucidworks Fusion experience over any other search platforms. Travel Requirement:
Limited, as needed. Only W2 candidates are eligible for this position. Third-party or C2C candidates will not be considered.

Job Description:

Scope of Position Lead the design, build, tuning, and operation of the search layer for client. The role delivers secure, grounded, and supportable conversational search using Lucidworks Fusion or a comparable enterprise search platform, with an initial single-turn answer experience followed by multi-turn conversational search. Translate customer and business needs into scalable index and query pipelines across web, content, commerce, and AI platforms.

This contract role is an alternative to external professional services and requires hands-on technical delivery as well as solution leadership. Responsibilities
1. Search Platform and Retrieval Engineering Design and implement collections, schemas, connectors, index/query pipelines, query profiles, and REST API integrations in Lucidworks Fusion or an equivalent platform. Build and tune lexical, semantic, vector, and neural hybrid retrieval, including embeddings, blend weights, thresholds, boosting, filters, facets, synonyms, and fallback behavior. Use signals and behavioral data to improve relevance, recommendations, personalization, and popular or successful results.

Create relevance benchmarks, automated regression tests, citation and grounding tests, latency targets, and per-query cost measures. Troubleshoot ingestion, indexing, Solr, Kubernetes/AWS, APIs, pipelines, model endpoints, and front-end integrations.
2. Conversational Search and Generative AI Engineer single-turn and multi-turn search flows with intent recognition, entity extraction, query rewriting, clarification, and session context. Implement grounded RAG that retrieves approved sources, cites evidence, and suppresses or falls back when evidence or confidence is insufficient. Integrate with enterprise LLM services and client's AI Gateway using prompt controls, model configuration, rate limits, error handling, latency budgets, and cost governance.

Tune experiences for product numbers, specifications, availability, certificates, manuals, application notes, and related support content. Apply guardrails for transactional or product-SKU queries, low-confidence grounding, and zero-result scenarios.
3. Integration, Delivery, and Operations Partner with AEM and front-end engineers to deliver accessible search results, conversational answers, follow-up suggestions, and facets aligned with the client Design System. Manage Fusion configuration as code through Git Lab, peer review, automated testing, and CI/CD practices. Instrument click-through, zero-result, no-click, reformulation, abandonment, task completion, latency, and pipeline-health metrics. Produce architecture diagrams, deployment documentation, runbooks, configuration standards, and…