GenAI Solution Engineer (Databricks AI/Snowflake AI pref'd)
Indexed description
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Recruiting for this role ends on 5/29/2026
Role Summary
We're seeking a GenAI practitioner who can embed with Deloitte client teams and use Claude / Codex / Gemini using various IDEs to solve real business problems-rapidly prototyping solutions, writing production-quality code, and enabling client and Deloitte teams to adopt GenAI safely and effectively. You'll operate at the intersection of AI engineering, data engineering/data science, and delivery, translating ambiguous needs into working software and measurable outcomes.
Work you'll do
- Client Delivery (Forward-Deployed)
- Embed with Deloitte client teams to identify high-value use cases and translate them into executable GenAI solutions
- Lead rapid discovery, prototyping, iteration, and deployment-moving 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 appropriate 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 that help teams scale adoption.
- Engineering & Data Foundations
- Write and ship code that integrates Claude / Codex / Gemini via APIs into client systems, workflows, and data platforms
- Build or enhance data pipelines and features that power Claude / Codex / Gemini use cases (e.g., document ingestion, metadata, embeddings, search)
- Apply strong practices in testing, logging/monitoring, versioning, and CI/CD to support production-grade releases
- Enablement & Change Adoption
- Coach client and project teams on how to use Claude / Codex / Gemini effectively (prompt patterns, workflows, evaluation, governance)
- Create reusable assets (playbooks, reference architectures, example repos, demo flows) to accelerate future delivery
- Communicate complex technical concepts clearly to non-technical audiences through concise storytelling and visuals
Qualifications
Required:
- At least 4 years of relevant professional consulting or industry role experience in data engineering, data science, analytics engineering, or software engineering (experience level flexible based on role leveling)
- 2+ years hands-on experience building with generative AI and LLMs; to include experience leveraging Claude, Codex and/or Gemini to deliver working solutions (ie: prompt patterns, workflows, evaluation, governance
- 2+ year's hands-on Python and SQL experience; including experience building reliable, maintainable code
- 1+ years experience leading project workstreams/engagements 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, based on the work you do and the clients and industries/sectors you serve
- Limited immigration sponsorship may be available
- Experience with:
- Snowflake including hands-on experience with one of the following key platforms: Cortex AI, Cortex LLM Functions, Cortex Agents, Arctic Embed
- Databricks including hands-on experience with one of the following key platform technologies: DBRX, MLflow, Vector Search, Databricks AI Gateway
- Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
- Data engineering experience with: Spark, Airflow/dbt, streaming, data modeling, observability; and/or data science experience with feature engineering, ML, and experimentation
- Experience with vector databases and search (e.g., embeddings, hybrid search) and building RAG pipelines end-to-end
- Experience with MLOps/LLMOps practices (ie: evaluation frameworks, monitoring, prompt/version management, model governance)
- Experience integrating LLM solutions with enterprise systems (ie: APIs, microservices, event-driven architectures)
- Experience with security, privacy, and responsible AI considerations in regulated environments
- Experience developing impactful collateral for client workshops and interactive customer sessions, driving alignment and actionable outcomes
- Experience presenting to both large and small audiences
- An advanced degree in the area of specialization
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
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