Resillion
Website:
resillion.com
Company:
https://www.linkedin.com/company/resillion
Seniority: Mid-Senior level
Industries: IT Services and IT Consulting
Job details:
Company Description
Resillion helps organisations build technology they can trust. Our work matters because today’s digital world is connected and increasingly complex. From software and platforms to devices, media, AI and critical business systems, our teams help clients make sure their products and services work as they should.
We’re the only company who combine quality engineering, cyber security, conformance and interoperability, and media content quality control into something we call Total Quality. We combine human insight with advanced AI to deliver solutions that support performance from concept to launch.
Resillion is also a place to grow. We're a team of curious, collaborative experts who care about doing things well. You’ll be trusted to bring your ideas, take ownership and keep learning, with support from colleagues across our global business. We value expertise and the different perspectives people bring - creating an environment where you can build a career with confidence.
Job Title: Lead Software Engineer
Experience Range: 6-10 Years
Location: Bangalore/Hybrid
Direct Reports: Yes
About the role:
As a Lead Engineer, you will own the ongoing delivery of our broadcast and hybrid-TV compliance product set — the tools and test suites that verify HbbTV, CI+ and ATSC conformance for broadcasters, TV manufacturers and standards bodies worldwide. Your primary focus is shipping reliable enhancements and bug fixes across this product set, working within an AI-led, agentic software delivery lifecycle. That AI-augmented way of working is led and initially implemented by the Bristol team; this role takes it on to maintain and develop, while product delivery remains the priority. This is a hands-on technical leadership role.
Roles and Responsibilities:
- Ship reliable enhancements and bug fixes across our HbbTV, CI+ and ATSC compliance tools and test suites, owning quality from specification through to release.
- Translate broadcast conformance specifications into robust, maintainable software and automated tests — including checklist validation, emulated-device checks and traceable links between requirements, tests and evidence.
- Deliver within an AI-led, agentic SDLC: AI implements change from approved tickets and raises pull requests, while you and the team retain review, approval and merge accountability.
- Take on, maintain and evolve the AI-augmented engineering platform behind the product set — Azure DevOps CI/CD, pipelines, security scanning and release automation on Azure.
- Feed a continuous-improvement learning loop, using AI to turn failures and recurring issues into backlog-ready improvements.
- Act as a player-coach: mentor engineers, set coding, architectural and responsible-AI-usage standards, support hiring and unblock complex technical challenges.
- Work with globally distributed teams across the UK, India, China and Belgium.
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Required Skills
- Strong software engineering background using Python, Django and Linux.
- Proven experience delivering and maintaining software and automated test suites for broadcast or hybrid-TV compliance, ideally HbbTV, CI+ or ATSC.
- Ability to analyse broadcast conformance specifications and turn them into reliable software and tests.
- Comfortable delivering within an AI-led, agentic SDLC (AI coding assistants, automated PR generation) with strong human-in-the-loop review and quality control.
- Hands-on experience running CI/CD on Azure DevOps — pipelines, build/release automation and security scanning — on Azure cloud infrastructure; Git and modern source-control workflows a given.
- Working knowledge of Jira and modern SDLC tooling; familiarity with Redmine an advantage.
- Strong engineering judgement to validate AI outputs against specifications and architectural standards.
Use of AI & Modern Engineering Practices
- Use AI-assisted tools responsibly to accelerate development, testing, debugging, and documentation tasks.
- Apply strong engineering judgement to validate AI outputs, ensuring quality, correctness, and alignment with specifications and architectural standards.
- Lead by example in identifying opportunities where AI can improve team productivity, consistency, and quality without compromising technical rigour.
Click on Apply to know more.