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Senior AI, Data & Machine Learning Engineer

DD Consulting Pty Ltd    Colombo • Full-time

DD Consulting builds custom AI workflows, enterprise data pipelines, SaaS automation platforms, and cloud infrastructure for growing enterprise clients across Australia and New Zealand. We are seeking a Senior Lead AI, Data & Machine Learning Engineer to take technical ownership of our data systems, AI product engine, and client solution design.

In this role, you will bridge scalable Data Engineering (ETL/ELT, vector infrastructure, structured data processing) with modern Generative AI (LLM orchestration, RAG, Agentic workflows), applied Machine Learning, and Computer Vision. Beyond core development, you will analyze business processes to solution AI-driven enhancements, produce clear system and multi-agent architecture diagrams, and build cost estimation models for cloud compute and LLM token usage.

Key Responsibilities

  • AI Process Solutioning & Architecture Design: Evaluate complex client business workflows to identify automation opportunities. Create production-ready architecture diagrams (system topology, data flows, multi-agent networks) and deliver accurate cost estimations covering cloud infrastructure, API tokens, and GPU compute.
  • Generative AI & Agentic Workflows: Architect and deploy production-grade LLM integrations using AWS Bedrock, OpenAI, and Anthropic Claude. Build stateful, multi-agent networks and autonomous workflows using frameworks like LangGraph, CrewAI, or LlamaIndex.
  • Data Architecture & Vector Systems: Design and maintain scalable data pipelines, data modeling frameworks, and hybrid search architectures using vector engines (Pinecone, PGVector, Qdrant) alongside SQL/NoSQL databases.
  • Computer Vision & Visual ML: Build, train, and deploy Computer Vision pipelines using PyTorch, OpenCV, YOLO, and Vision-Language Models (VLMs) for object detection, image segmentation, and visual data processing.
  • Model Fine-Tuning & Applied ML: Lead dataset curation, data cleaning, training, and parameter-efficient fine-tuning (LoRA, QLoRA, PEFT) for domain-specific models.
  • Backend & Cloud Infrastructure: Write high-performance microservices in Python or TypeScript/Node.js. Deploy serverless and containerized infrastructure on AWS (Lambda, API Gateway, S3, ECS, Docker) with automated CI/CD and MLOps observability.
  • Technical Governance & Cost Control: Benchmark LLM latency, output accuracy, and pipeline throughput while enforcing enterprise security standards, code reviews, and token/compute cost optimization.

Requirements & Technical Depth

  • Core Technical Stack: 5+ years of software/data engineering and machine learning experience with deep proficiency in Python and solid working knowledge of Node.js/TypeScript.
  • Solutioning & System Design: Demonstrated ability to translate raw business requirements into structured AI solutions, technical diagrams (multi-agent, data pipeline, and system workflows), and detailed infrastructure cost models.
  • Data & AI Stack: Proven experience with vector databases, stateful agent frameworks, computer vision libraries (OpenCV, PyTorch, YOLO), LLM fine-tuning, and RAG architectures.
  • AWS Cloud Expertise: Hands-on experience building, deploying, and monitoring data/AI services on AWS (Lambda, S3, API Gateway, ECS, Bedrock).
  • AWS Certifications (Preferred): AWS Certified Solutions Architect (Associate or Professional), Data Engineer – Associate, or AWS Generative AI – Specialty is strongly preferred (focus will be placed on obtaining/validating certification during Month 1 if not already held).
  • Communication & Overlap: Fluent English communication (B2/C1+) with guaranteed availability during Australian Business Hours (AEST/AEDT).