Jobs in India

Technical Implementation Manager in India

1,322 active opportunities · Updated October 2026

Explore current technical implementation manager jobs across India. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 India· Full-time
✓ Quality checkedCompany trend -71.5%

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. About the Team Okta's Core Engineering team is responsible for building and evolving shared infrastructure and services that lay the foundation for what other engineering teams build on. We're in charge of common shared services like distributed cache, configuration management, frameworks for async job management, internal tooling for developer support, and email pipeline, to name a few. We're cloud native, where redundancy, multi-tenancy, scale, resource optimization and resiliency are first class citizens. With Okta's mantra of 'Always On!' there's never a dull moment. Our biggest asset is our team of passionate engineers and technically minded managers. Role: This is an opportunity for an experienced Backend engineer to join our growing Core Platform team based out of Bengaluru. In this role, you will get to work with highly skilled and talented engineers throughout the organization to build and manage some of the critical platform services powering Okta’s products and infrastructure. This role requires a blend of high-level architectural thinking and hands-on execution to build resilient, high-performance backend services. We are not only passionate about building services but operating them at scale, making them resilient to provide a seamless service to our customers. You'll be leading a team of highly skilled and talented team players who're proud of what they own and deliver. Our elite team is fast, creative and flexible; with a weekly release

JavaSQLMySQLRedis
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Relocation support. Relocation assistance is stated. This does not establish visa sponsorship.
📍 India· Full-time
✓ Quality checkedCompany trend -94.2%

About the Team Our Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. Within Safety Systems, the Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. About the Role If you have a specific expertise or speciality related to this work, please note it in your application via your resume, cover letter or application note. Frontier AI systems are expanding what people can do across domains, creating both enormous opportunities and difficult safety questions: when should a model help, when should it refuse, and how do we make those boundaries clear enough to train, evaluate, and enforce? In this role, you will help define how OpenAI’s models should behave in high-risk or high-ambiguity contexts, such as agentic systems, multimodal systems, user safety, privacy, and other emerging risk domains. This is an ideal role for someone who can move across unfamiliar topics, reason from first principles, and turn ambiguity into practical model behavior. You will work closely with research, engineering, product, preparedness, and operations teams to build policies that are technically grounded, measurable, and responsive to real-world risk. In this role, you will: Design and maintain model policies across safety-relevant domains, including dual-use, agentic, and emerging frontier-risk areas. Translate risk and harm models into clear behavioral specifications, evaluation criteria, grading guidance, and system-level safeguards. Define practical boundaries between beneficial uses of AI and assistance that could materially enable harm, exploitation, misuse, or unsafe outcomes. Build policy artifacts that support model training, evaluation, and deplo

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