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Company Overview
A leading global professional services organization is seeking a senior Forward Deployed Engineer to help clients implement AI and GenAI solutions at enterprise scale. The organization specializes in technology consulting, AI, data engineering, and digital transformation, delivering high-impact solutions across industries and enabling clients to modernize operations while driving innovation.
Position Summary
The Lead Forward Deployed Engineer (FDE) serves as a senior practitioner embedded with strategic clients, leading engineering pods to design, build, and deploy AI and GenAI solutions. This role combines technical leadership, client engagement, and hands-on engineering to ensure production-grade results and measurable business impact.
Responsibilities
Client Engagement
Serve as the senior client-facing engineering partner, building trusted advisor relationships with product, data, and platform leaders
Lead executive-level discovery, define success metrics (quality, latency, cost, adoption, risk), and create phased plans from prototype to production
Navigate organizational complexity to align executive sponsors, IT leadership, and business owners on shared AI initiatives
Represent FDE capabilities in client pursuits, executive briefings, and platform partner engagements
Cross-Functional Pod Leadership & Program Governance
Lead FDE pods of 2–5 engineers, managing execution, resources, escalations, and delivery health
Enforce delivery standards across sprints, stakeholder communication, risk management, and quality gates
Coordinate multi-pod or multi-workstream engagements to ensure consistent architecture and client experience
Mentor and develop junior FDEs
GenAI Solution Development
Architect and oversee LLM-enabled applications including copilots, assistants, agentic workflows, and knowledge search experiences
Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls
Govern end-to-end RAG pipeline design including ingestion, chunking, embedding, vector retrieval, and hybrid search
Guide architecture of data pipelines powering GenAI solutions
Enforce strong data management, testing, CI/CD, logging, versioning, and documentation practices
Maintain deep familiarity with cloud environments such as AWS, Azure, and Google Cloud
Required Qualifications
Bachelor’s degree (or equivalent) in Computer Science, Data Science, or Engineering
7+ years of experience in software engineering, data engineering, data science, or analytics engineering
1+ years hands-on experience building and deploying GenAI/LLM solutions in production or client environments
1+ years experience with Microsoft AI & Data, including Azure AI Foundry
1+ years leading project workstreams and translating business problems into AI solutions
Experience building reliable, maintainable, and well-documented code
Ability to travel up to 50% depending on client and project needs
Preferred Qualifications
Experience with cloud environments (AWS, Azure, Google Cloud) and common services (storage, compute, IAM, networking)
Experience working directly with client technical teams in fast-paced, ambiguous delivery environments
Data engineering experience with Spark, Airflow/dbt, streaming, data modeling, or ML feature engineering and evaluation
Experience with MLOps/LLMOps practices including evaluation frameworks, model monitoring, and prompt management
Integration of LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures
Experience operating in hybrid onshore/offshore teams
Familiarity with security, privacy, and compliance considerations
Disclaimer
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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.
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