Senior Full Stack Engineer (AI-Enabled Solutions)

Role Overview

We are looking for a client-facing Senior Full Stack Engineer to own end-to-end solutions across application development, AI-enabled capabilities and cloud infrastructure.

The role involves working directly with clients to understand business requirements, identify suitable AI use cases, design architectures, deliver solutions and support them in production.

You will work with Java, Spring Boot, React and AWS, integrating managed AI services where they add measurable value. This is a hands-on engineering and delivery role involving client engagement, technical leadership and coordination of remote development teams.

Key Responsibilities

Client Engagement and Solutioning

• Understand client business processes, pain points and application requirements.
• Conduct requirement workshops and translate business needs into functional and technical specifications.
• Assess AI use cases and recommend appropriate solutions, including deterministic logic, workflow automation or AI-assisted capabilities.
• Define acceptance criteria covering quality, security, performance, cost and fallback behaviour.
• Design application, data, integration, AI and AWS architectures, presenting options and trade-offs to stakeholders.
• Act as the client's trusted technical advisor.

Delivery and Project Management

• Own end-to-end project delivery, including scope, planning, timelines, risks and reporting.
• Manage Agile ceremonies and coordinate remote development teams.
• Assign tasks, review progress, resolve blockers and manage change requests.
• Ensure alignment on scope, budget and delivery expectations.
• Prepare technical documentation, runbooks and handover materials.

Application and AI Engineering

• Design and develop backend services, microservices and REST APIs using Java and Spring Boot.
• Build responsive frontends using React, Redux and Tailwind CSS.
• Design data models and integrate databases, third-party systems and client APIs.
• Develop serverless and event-driven solutions using AWS Lambda and Step Functions.
• Integrate managed AI services, primarily Amazon Bedrock and, where appropriate, Amazon SageMaker.
• Build RAG workflows using S3, Lambda, Step Functions and vector-search solutions such as Amazon OpenSearch Service or Aurora PostgreSQL with pgvector.
• Implement source citations, metadata filtering, access controls and secure AI integrations.
• Develop AI-enabled user experiences with streaming responses, feedback capture and human confirmation.
• Implement automated AI evaluations covering quality, groundedness, safety, latency and cost.
• Conduct code reviews and establish engineering standards for quality, security and performance.

Cloud Infrastructure, DevOps and Support

• Design, provision and manage AWS infrastructure, including S3, Lambda, Step Functions, EKS and managed AI services.
• Implement networking, security and access controls using VPC, IAM, encryption, KMS and secrets management.
• Deploy containerised workloads using Docker and Kubernetes.
• Implement Infrastructure as Code and CI/CD pipelines using Terraform or CloudFormation/CDK.
• Lead deployments, UAT and go-live activities.
• Provide production support, troubleshoot application, API, AI and infrastructure issues, and drive root-cause resolution.
• Establish monitoring, logging, tracing and alerting using tools such as CloudWatch.
• Ensure security, compliance, data protection, auditability and responsible AI practices.
• Maintain operational runbooks, fallback mechanisms and rollback procedures.

Required Skills and Experience

• 8+ years of software development experience, with at least 3 years as a Full Stack Engineer or Technical Lead.
• Proven client-facing experience in requirements gathering, solution design and stakeholder management.
• Experience managing project delivery and coordinating remote or offshore teams.
• Practical experience integrating or supporting at least one AI-enabled application or pilot, preferably on AWS.
• Working knowledge of RAG, prompt engineering, embeddings, vector search, tool/function calling, automated evaluation and AI guardrails.
• Ability to explain AI limitations and technical trade-offs to clients and translate them into practical requirements.

Technical Skills

• Backend: Java (11+), Spring Boot, Spring Security, REST APIs, microservices, JPA/Hibernate.
• Frontend: React, Redux/Redux Toolkit, Tailwind CSS, JavaScript/TypeScript, HTML5.
• AWS: S3, Lambda, Step Functions, EKS, Bedrock, SageMaker, IAM, VPC, API Gateway, RDS/Aurora, DynamoDB, SQS/SNS, EventBridge, CloudWatch, ECR, Secrets Manager, KMS and OpenSearch Service.
• AI Engineering: RAG, prompt and context design, embeddings, vector search, tool/function calling, automated evaluation and guardrails.
• AI Data and Operations: S3-based knowledge ingestion, OpenSearch or Aurora PostgreSQL/pgvector, prompt/model versioning, observability, cost and latency monitoring.
• Containers and DevOps: Docker, Kubernetes, Helm, Terraform or CloudFormation/CDK, CI/CD (GitLab CI, GitHub Actions or Jenkins), Git.
• Databases: PostgreSQL or MySQL and at least one NoSQL database.
• Delivery: Agile/Scrum, Jira/Confluence, estimation, risk and change management.

Candidates should be comfortable selecting appropriate AWS services and avoiding AI where simpler deterministic solutions are safer, clearer or more cost-effective.

Nice to Have

• AWS certification (Solutions Architect Associate/Professional, Developer or DevOps Engineer).
• Experience with public sector or healthcare projects and government security standards such as IM8.
• Knowledge of healthcare data standards such as HL7 or FHIR.
• Experience with OAuth2/OIDC, Singpass/Corppass or other identity platforms.
• Familiarity with automated testing (JUnit, Jest, Cypress or Playwright) and SonarQube.
• Python experience for AI evaluation, data preparation or lightweight service development.
• Experience with SageMaker, MLOps, generative AI evaluation and observability.
• Experience delivering AI solutions in regulated environments.
• Project management certification (PMP, PRINCE2 or Certified ScrumMaster).

Qualifications and Soft Skills

• Bachelor's degree in Computer Science, Information Technology, Engineering or a related field.
• Strong verbal and written communication skills.
• Consultative mindset with the ability to understand business needs and propose practical solutions.
• Strong ownership and accountability for delivery outcomes.
• Leadership and mentoring skills, including coordinating engineers across time zones.
• Structured problem-solving skills and the ability to remain calm under production pressure.