Senior Data & AI Presales Engineer - AWS FDE

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