Role summary We're seeking a GenAI practitioner who can embed with 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 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
The team Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.
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
- 1+ years of experience with:
- Snowflake including hands-on experience with one of the following key platforms: Cortex AI, Cortex LLM Functions, Cortex Agents, Arctic Embed
and/or
- Databricks including hands-on experience with one of the following key platform technologies: DBRX, MLflow, Vector Search, Databricks AI Gateway
- 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 (or equivalent experience) 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
Preferred: - 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
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $113,100 to $208,300.
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.
