Senior Data & AI Presales Engineer - AWS FDE

Accenture Southeast Asia; Singapore; On-site; SGD 120,000 - 160,000; Full time

Job summary

Accenture Southeast Asia is seeking a Senior Data & AI Presales Engineer to act as a Forward Deployed Engineer, working directly with clients to originate, shape, and win AI and data transformation opportunities.

The role requires hands-on engineering, rapid prototyping, and the ability to lead small teams to deliver end-to-end solutioning and pre-sales execution in Singapore.

Qualifications

• 8–15+ years in data engineering, AI/ML, or cloud engineering.
• Experience in enterprise or financial services is preferred.
• Strong hands-on AWS data & AI technologies.
• Proven client-facing presales / solutioning background.
• Ability to build live demos and PoCs under time pressure.

Responsibilities

• Lead client-facing discovery workshops and technical discussions.
• Design and build AWS-based data and AI solutions.
• Develop live demos, PoCs, and rapid prototypes.
• Coordinate small technical teams for end-to-end solutioning.

Skills

Presales mindset

Python programming

Client engagement

Prototyping

Tools

AWS

SageMaker

Redshift

Glue

Lambda

ECS/EKS

Job description

• Customer analytics / recommendation engines
• AWS Data & AI Engineering (Hands-on)

Data Engineering

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

• 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
• 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
  • 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 behavior: Build, test, and refine solutions in the client environment and context

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
  • 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

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
• 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