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 Qualificati