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GenAI Solution Engineer (Databricks AI/Snowflake AI preferred)

SpringCube

Full time - Senior Engineer

IT Services & Consulting

United States, Boston - Massachusetts

Published 3 weeks ago

Salary: Disclosed upon interview

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Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview
A leading global professional services organization is seeking a GenAI Solution Engineer to help clients transform technology platforms, accelerate digital initiatives, and deliver measurable business impact. The company provides end-to-end AI, data, and analytics solutions, combining deep engineering expertise with innovative technologies to enable clients to modernize operations and scale digital transformation efforts across multiple industries.

Role Summary
The GenAI Solution Engineer will embed with client teams to rapidly prototype, build, and deploy generative AI solutions using Claude, Codex, and Gemini. This role operates at the intersection of AI engineering, data engineering, and delivery, translating complex business needs into scalable, production-ready software while driving adoption of GenAI tools safely and effectively.

Work You’ll Do

Client Delivery (Forward-Deployed)

  • Embed with client teams to identify high-value use cases and translate them into executable GenAI solutions
  • Lead rapid discovery, prototyping, iteration, and deployment from concept to production with strong engineering discipline
  • Partner with business and technical stakeholders to define success metrics, constraints, and rollout plans

GenAI Solution Development (Claude / Codex / Gemini)

  • Build LLM-enabled applications such as copilots, assistants, workflow automations, and knowledge search experiences
  • Develop and maintain prompts, tool-use patterns, and agentic workflows with human-in-the-loop controls
  • Implement retrieval-augmented generation (RAG) and evaluation approaches (quality, hallucination risk, safety, latency, cost)
  • Establish usage patterns, templates, and guardrails to help scale adoption

Engineering & Data Foundations

  • Write and ship code integrating Claude / Codex / Gemini via APIs into client systems, workflows, and data platforms
  • Build or enhance data pipelines and features powering GenAI use cases (e.g., document ingestion, metadata, embeddings, search)
  • Apply best practices in testing, logging/monitoring, versioning, and CI/CD for production-grade releases

Enablement & Change Adoption

  • Coach client and project teams on effective use of Claude / Codex / Gemini (prompt patterns, workflows, evaluation, governance)
  • Create reusable assets (playbooks, reference architectures, example repos, demo flows) to accelerate delivery
  • Communicate complex technical concepts clearly to non-technical audiences through storytelling and visuals

Qualifications

Required:

  • 4+ years professional consulting or industry experience in data engineering, data science, analytics engineering, or software engineering
  • 2+ years hands-on experience with generative AI and LLMs (Claude, Codex, and/or Gemini) including prompt design, workflows, evaluation, and governance
  • 2+ years hands-on Python and SQL experience, building reliable, maintainable code
  • 1+ year experience leading project workstreams and translating business problems into AI solutions
  • Bachelor’s degree in Computer Science, Data Science, Engineering, or related field
  • Ability to travel up to 50% on average
  • Limited immigration sponsorship may be available

Preferred:

  • Hands-on experience with Snowflake platforms (Cortex AI, Cortex LLM Functions, Cortex Agents, Arctic Embed)
  • Hands-on experience with Databricks technologies (DBRX, MLflow, Vector Search, Databricks AI Gateway)
  • Experience with cloud environments (AWS, Azure, GCP) and platform services (storage, compute, IAM, networking)
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling, observability
  • Data science experience with feature engineering, ML, and experimentation
  • Experience with vector databases and search, building RAG pipelines end-to-end
  • MLOps/LLMOps practices including evaluation frameworks, monitoring, prompt/version management, and model governance
  • Integration of LLM solutions with enterprise systems (APIs, microservices, event-driven architectures)
  • Knowledge of security, privacy, and responsible AI in regulated environments
  • Experience developing client workshop materials and presenting to audiences of varying sizes
  • Advanced degree in relevant specialization is a plus

Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals in globally.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job.
4. No Liability: SpringCube is not liable for inaccuracies.