Senior Full stack Engineer

Position Responsibilities

As a

Senior Software Engineer in Java , you will:

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Lead hands-on architecture, design, and implementation of agentic applications, AI-powered services, and platform capabilities from concept through production

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Define engineering patterns and best practices for production AI systems, including evaluation, monitoring, guardrails, resiliency, cost control, and rollback strategies

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Drive end-to-end software delivery across the SDLC, from discovery and prototyping to testing, release, and production operations

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Use engineering tools to accelerate design, coding, testing, documentation, troubleshooting, and delivery while maintaining strong engineering judgment and code quality standards

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Champion an AI-enabled SDLC by improving developer workflows, automation, test generation, code review quality, release confidence, and team productivity

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Partner closely with Product, Applied AI, Data Science, and business stakeholders to translate ambiguous opportunities into scalable product capabilities

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Provide technical leadership through architectural decisions, design reviews, code reviews, hands-on contribution, and mentoring of engineers across the team

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Build highly available, secure, and maintainable cloud-native services with strong observability, performance, and operational readiness

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Shape technical roadmaps, identify short- and long-term platform needs, and influence architecture choices that enable scale, reuse, and faster delivery

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Collaborate across teams and business units to solve complex business and engineering problems with practical, high-impact solution

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Keep senior stakeholders informed of progress, risks, trade-offs, and implementation decisions in a clear and concise manner

Requirements

Ideal Candidate Qualifications:

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Strong software engineering experience building scalable, secure, maintainable production systems, including experience leading complex technical initiatives end to end

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Hands-on experience building and shipping AI-powered products or agentic applications using LLMs, orchestration frameworks, tool-calling patterns, retrieval, and context-aware workflows

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Strong understanding of agentic system design, including planning, reasoning loops, workflow orchestration, memory, grounding, evaluation, safety, and human-in-the-loop controls

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Experience taking AI solutions from prototype to production with sound engineering discipline around reliability, observability, latency, cost, security, and governance

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Experience with modern AI frameworks, SDKs, and tooling for building AI applications, agent workflows, and developer productivity use cases

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Strong programming skills in one or more backend languages such as

Java 17+,

and Python, with the ability to write high-quality, well-tested, production-ready code

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Experience with modern front-end frameworks such as React and/or Next.js for building intuitive product experiences would be beneficial

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Experience building services in cloud-native environments using Kubernetes and managed cloud services on AWS, Azure

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Good understanding of APIs, distributed systems, event-driven architectures, data pipelines, and integration patterns across enterprise platforms

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Experience with CI/CD, automated testing, and engineering automation, including the ability to improve SDLC efficiency and release quality using AI tools

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Practical experience using AI coding and engineering assistants to improve productivity across design, implementation, testing, debugging, documentation, and operational support

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Strong background in software security, including authentication, authorisation, secrets management, encryption, threat modelling, and secure deployment practices for AI-enabled systems

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Proven ability to create reusable platforms, frameworks, or internal engineering capabilities that improve developer experience and accelerate delivery across teams

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Strong product mindset with the ability to translate user needs and business goals into practical, high-impact technical solutions

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Excellent collaboration and communication skills, with experience influencing across engineering, product, data science, and leadership stakeholders

Requirements

Bucket

Skills / Metrics

Must-Have

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Strong hands-on programming expertise in Java and Python, with the ability to design, build, test, and optimise production-grade backend services

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Strong experience with React for building modern, responsive, and intuitive user interfaces for enterprise applications

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Experience with Next.js or modern front-end architecture patterns alongside React

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Deep experience building cloud-native applications using containers, Kubernetes, microservices, and managed cloud services in AWS and/or Azure

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Strong expertise in designing and building APIs, including RESTful services, service contracts, versioning, security, and integration patterns

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Proven experience with event-driven architecture, asynchronous messaging, streaming, and resilient distributed system design

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Practical experience using AI tools to improve engineering productivity across coding, testing, debugging, documentation, and release workflows

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Strong understanding of software engineering quality metrics such as code quality, test automation, reliability, performance, observability, and maintainability

Good to Have

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Experience building agentic applications or AI-powered systems using LLMs, orchestration frameworks, retrieval, tool calling, and workflow automation

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Experience with API gateway, service mesh, and enterprise integration patterns

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Experience with Kafka, event streaming platforms, or large-scale messaging ecosystems

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Exposure to CI/CD automation, infrastructure as code, and release engineering practices

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Experience in regulated enterprise environments where security, governance, compliance, and auditability are critical

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Ability to mentor engineers and influence architecture, engineering standards, and developer productivity at team level

All About You

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You are a hands-on technical leader who enjoys building and shipping real products, not just prototypes

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You have experience building or operating AI-enabled or agentic applications in production and understand what it takes to make them secure, reliable, and useful at scale

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You combine strong software engineering fundamentals with curiosity and good judgment in applying emerging AI capabilities to real business problems

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You actively use AI to enhance your own engineering productivity and help teams adopt better ways of designing, coding, testing, documenting, and operating software

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You understand where AI can accelerate delivery and where human review, engineering discipline, and thoughtful controls remain essential

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You care deeply about customer value, developer experience, quality, resilience, and long-term maintainability

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You are comfortable working in collaborative, cross-functional, and internationally distributed teams

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You raise the bar for others through mentorship, technical leadership, and a practical, delivery-focused mindset

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You communicate complex technical concepts clearly and effectively to both engineering teams and senior stakeholders