Senior Machine Learning Engineer

SenzMate IoT Intelligence eliminates the inequality in access for the best quality state-of-the-art IoT and AI technologies all around the world. We've always had a core mission to invent and innovate with the most advanced technologies, helping our clients become enterprises of the future and leaders in their industries. For the last 7 years, the essence of our company and culture has been built by the incredible people of SenzMate – where our many humanitarian contributions reflect our values.

As a senior engineer at SenzMate, you will work at the intersection of software engineering, artificial intelligence, and agentic coding. You will evaluate and implement emerging AI-powered development tools and build production-ready AI solutions that help modernise and transform complex enterprise software systems. We are looking for someone with senior-level engineering experience and a deep understanding of software development who can independently navigate complex codebases, identify technical risks, make sound architectural decisions, and deliver solutions without extensive hand-holding.

You should have strong hands-on experience with modern AI coding and agentic development tools and be comfortable evaluating and working with tools such as Claude Code, Cursor, GitHub Copilot, Windsurf, and similar technologies. This role will involve both technical assessment and hands-on implementation, ranging from evaluating AI coding agents against large enterprise codebases to architecting and developing AI-powered internal tools and agent orchestration systems.

Responsibilities

• Evaluating AI coding tools (Claude Code, Cursor, GitHub Copilot, Windsurf, etc.) against large enterprise codebases and documenting capabilities, limitations, and failure modes
• Running structured experiments – testing how AI agents handle tech debt remediation, code modernisation, dependency upgrades, and test coverage generation across real repositories
• Building AI-powered internal tools – chatbots, automated migration agents, code generation pipelines – as the engagement evolves from assessment to implementation
• Architecting agent orchestration systems that work across multiple codebases and tech stacks, developing production-quality solutions, not just proofs of concept
• Building AI enablement frameworks – CLAUDE.md configuration files, prompt templates, agent workflow documentation, and developer playbooks
• Conducting codebase assessments – dependency mapping, tech debt identification, and architecture documentation for legacy systems
• Producing client-ready technical reports, evaluation summaries, comparison analyses, and recommendation documents
• Researching emerging tools, techniques, and best practices in AI-assisted software development
• Setting up testing environments, managing repos, and configuring CI/CD integrations for AI tool evaluation
• Collaborating with the engineering team on implementation and knowledge transfer

Technical skills

• Strong hands-on experience with Python and JavaScript/TypeScript
• Deep understanding of Git, including branching strategies, pull request workflows, merge management, and repository practices
• Hands-on, production-level experience using AI coding and agentic development tools, such as Claude Code, Cursor, GitHub Copilot, Windsurf, or similar tools
• Ability to navigate, understand, and analyse large and unfamiliar codebases across multiple programming languages, frameworks, and technology stacks
• Strong experience with CI/CD pipelines, including GitHub Actions, Jenkins, GitLab CI, or similar technologies
• Strong software architecture skills, with the ability to design, evaluate, and modify system architectures when required
• Proven experience building production backend services and APIs, rather than only scripts, experiments, or prototypes
• Strong understanding of REST APIs, database integration, service architecture, and production software development
• Experience building AI-powered applications, such as chatbots, agent orchestration systems, automated workflows, code generation systems, or AI-enabled developer tools
• Ability to design and implement reliable software solutions that integrate AI capabilities into existing systems and development workflows

Soft skills

• Ownership mentality: you take strategic direction and independently figure out the how, the edge cases, and the risks without detailed task breakdowns
• Excellent written English; your documentation will go directly to senior engineering leadership. It must be clear, structured, and client-ready without rewriting
• Speed – you ship 80% fast, iterate, and deliver. You don't spend three days perfecting a setup before producing anything
• Proactive communication: you flag risks, propose solutions, and surface insights without being asked
• Intellectual curiosity: you're genuinely interested in how AI is changing software development, not just executing tasks related to it

Qualifications

• 3+ years of professional experience in a senior software engineering, AI engineering, or closely related role
• Experience working as a senior engineer or tech lead on at least one large-scale modernisation, migration, transformation, or enterprise software project
• Strong understanding of enterprise software systems, including complex, legacy, multi-team codebases – not only clean or greenfield startup environments
• Demonstrated ability to independently understand complex technical problems and determine appropriate solutions without detailed task breakdowns
• Experience delivering software that is used and depended upon by other teams, customers, or production systems

Nice to Have

• Familiarity with LLM APIs, including Claude API, OpenAI API, or similar platforms
• Experience with developer platforms such as Backstage or Spotify-style internal developer portals
• Knowledge of CLAUDE.md, AGENTS.md, and other AI agent configuration and instruction patterns
• Experience with code quality, security, SAST, and SCA tools
• Experience with AI agent frameworks, orchestration patterns, or automated software engineering workflows
• Experience working with cloud platforms and modern infrastructure environments