Senior Data & AI Presales Engineer (AWS | Forward Deployed Engineer)
Role Summary
We are seeking a Senior Data & AI Presales Engineer to act as a Forward Deployed Engineer (FDE)—working directly with clients to originate, shape, and win AI & data transformation opportunities.
This is a high-impact, hands-on, client-embedded role requiring the ability to:
- Engage clients to identify and shape high-value AI/data use cases
- Design and build AWS-based solutions aligned to business outcomes
- Develop live demos and prototypes on the spot to accelerate deal conversion
- Lead small teams to deliver end-to-end solutioning and pre-sales execution
The ideal candidate combines strong engineering capability, presales instincts, and rapid prototyping expertise.
✅ Key Responsibilities
1. Forward Deployed Engineering (Client-Embedded Role)
- Work directly with client stakeholders (business + IT) to:
- Identify use cases and problem statements
- Validate technical feasibility and solution fit
- Act as a technical co-pilot during deal shaping, iterating solutions in real time
- Rapidly adapt solutions based on:
- Client feedback
- Data availability
- Business constraints
✅ Expected behavior: Build, test, and refine solutions in the client environment and context
2. Client Engagement & Deal Origination
- Lead:
- Discovery workshops
- Technical solution discussions
- Architecture deep-dives
- Translate business challenges into:
- AI/data use cases
- Executable solution designs
- Support:
- Opportunity creation and qualification
- Proposal development and technical response
3. Demo Engineering & Rapid Prototyping (Critical)
- Build live demos, PoCs, and proof-of-value solutions during client engagements
- Translate concepts into:
- Working applications
- API-driven services
- AI-enabled workflows
✅ Expected capability:
- Build a functional demo within hours/days, such as:
- GenAI assistants (RAG-based chatbots)
- AI-powered document processing (KYC, contracts)
- Customer analytics / recommendation engines
4. AWS Data & AI Engineering (Hands-on)
Data Engineering
- Design and build:
- Data lakes and pipelines (S3, Glue, Athena)
- Data warehousing solutions (Redshift, Aurora)
- Work with structured and unstructured enterprise data
AI / ML / GenAI
- Develop and integrate:
- Machine learning models (SageMaker)
- GenAI applications (Bedrock, LLM-based solutions)
- Implement:
- RAG pipelines
- Vector search and knowledge retrieval
Application Development
- Build cloud-native applications using:
- Lambda, ECS/EKS
- API Gateway, Step Functions
- Deliver end-to-end working solutions, not just architecture
5. Solutioning & Architecture Leadership
- Define:
- Solution architecture and patterns
- Technology stack and integration approach
- Ensure:
- Scalability, performance, and cost optimization
- Drive solution alignment with:
- Client KPIs and business outcomes
6. Team Leadership & Delivery Coordination
- Lead small technical teams for:
- Demo development
- Solutioning and proposal support
- Provide:
- Technical direction and quality assurance
- Collaborate with:
- Architects, data scientists, and delivery teams
✅ Required Qualifications
- 8–15+ years of experience in:
- Data engineering, AI/ML, or cloud engineering
- Enterprise or financial services environments
- Strong hands-on experience in:
- AWS data and AI technologies
- Designing and building cloud-based solutions
- Proven experience in:
- Client-facing presales / solutioning roles
- Engaging clients to shape and win deals
- Strong hands-on programming skills in Python, with ability to build:
- Data pipelines
- APIs and cloud-native applications
- AI/ML and GenAI prototypes
- Demonstrated ability to:
- Build live demos / PoCs under time pressure
- Translate ideas into working solutions quickly
✅ Preferred Qualifications
- Experience in:
- BFSI (banking, insurance, financial services)
- AI use cases (fraud, risk, personalization, customer 360)
- Hands-on experience with:
- GenAI frameworks (RAG, LangChain, orchestration tools)
- Streaming data / real-time processing
- AWS Certifications:
- Data Engineer / Machine Learning / Solutions Architect
✅ Key Success Profile
- Forward Deployed Engineer mindset — thrives in client-facing, fast-moving environments
- Strong builder mentality — able to code, prototype, and demo live
- Strong presales instinct — can originate and shape deals
- Able to bridge business needs with technical solutions
- Comfortable operating in ambiguity and rapid iteration cycles
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