Key Responsibilities

• Lead, mentor, and grow a high-performing team of AI/ML engineers, fostering a culture of innovation, collaboration, and excellence.
• Define and execute the roadmap for AI/ML projects, ensuring alignment with business objectives and product strategy.
• Architect and oversee the development of scalable, robust, and production-grade AI systems on cloud platforms (AWS, Azure, GCP).
• Drive best practices for the full machine learning lifecycle, including MLOps, CI/CD for ML, model monitoring, and governance.
• Collaborate closely with product managers, data scientists, and other engineering leaders to translate business requirements into technical solutions.
• Stay at the forefront of advancements in AI/ML, including Large Language Models (LLMs) and agentic AI, to identify and implement new opportunities.
• Manage project timelines, resources, and stakeholder communication to ensure the timely delivery of high-quality AI solutions.

Required Qualifications

• Strong understanding or experience leading AI/ML teams in a SaaS or enterprise software environment.
• Deep expertise in time series forecasting and machine learning.
• Experience architecting and deploying scalable, production-grade AI systems on cloud platforms (AWS, Azure, GCP).
• Solid understanding of MLOps, CI/CD for ML, and cloud-native architectures.
• Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
• Experience with agentic frameworks and autonomous agent architectures.
• Proficiency in Python and modern software development practices (testing, code review, CI/CD).
• Proven track record of delivering complex technical projects on time with high quality.
• Excellent communication, collaboration, and stakeholder management skills.
• Track record of delivering impactful AI solutions in a fast-paced, agile environment.

Preferred Qualifications

• Master’s or Ph.D. in Computer Science, AI, Machine Learning, or a related field.
• Experience with large-scale data processing frameworks like Spark.
• Familiarity with the challenges of applying AI in enterprise planning or financial domains.
• A portfolio of published research or contributions to open-source AI projects.

What Makes This Role Exciting

You will be a key leader in Anaplan’s AI journey, with the autonomy to shape our technical direction and build a world-class engineering team. This is a unique opportunity to solve complex, real-world problems and deliver intelligent solutions that empower major global enterprises to make more informed decisions. You will work with a passionate team on the cutting edge of AI, making a tangible impact on our product and the industry.

This new team will architect the platform foundation and infrastructure that enables a "build once, run anywhere" model, ensuring our AI-powered modernisation suite operates seamlessly regardless of a client's security or network constraints. We are looking for engineers to join this high-visibility initiative, where you will solve unique distributed systems puzzles and help shape the future of how global enterprises leverage GenAI.

We are looking for an experienced software engineer who thrives on solving infrastructure constraints and building enterprise facing platforms. 

The ideal candidate is a hands-on technical leader who can architect complex distributed systems, mentor engineers, and collaborate with product teams to deliver a platform that minimizes deployment friction and meets customers’ compliance requirements.

This role can be based out of our Gurgaon office or Remotely in India.

The ideal candidate for this role will have

• 8+ years of software development and operations experience, with a focus on building platforms and distributable software infrastructure.
• 2+ years of experience leading, coaching, and mentoring a team of engineers to achieve high-impact results.
• Deep experience designing distributable applications that run in air-gapped or highly restricted network environments.
• Strong proficiency in containerization and orchestration, with the ability to design systems where the host executes containerized applications under strict security monitoring.
• Experience building Service Host architectures that provide shared routing, proxy layers, and API gateways for multiple underlying services.
• Experience managing persistent storage solutions (blob/file storage) within distributed systems.
• Understanding of security-first design, specifically regarding the execution of untrusted code, fine-grain access control, and rigorous input validation.
• Experience designing auto-update mechanisms for software that cannot directly access the public internet.
• Curiosity, a positive attitude, and a drive to continue learning.

Position Expectations

• Provide technical leadership and mentorship to a team of engineers, fostering a culture of innovation, quality, and continuous improvement.
• Drive the distributed infrastructure for the Application Modernisation Platform, ensuring it supports a self-service SaaS product model while operating within client-controlled environments.
• Lead the design and implementation of a sophisticated orchestration layer that manages authentication, telemetry, and the lifecycle of modernization tools.
• Architect a client-side application that manages developer workflows and communicates securely with hosted services.
• Solve complex "Day 2" operations challenges, such as designing interfaces to solve DevOps challenges to manage users, secrets, and updates.
• Collaborate with security and product teams to ensure the platform can execute code generation and LLM-based tasks securely, protecting both client data and MongoDB IP.
• Act as a hands-on leader, guiding the team through technical challenges related to container security, local vs. hosted logic distribution, and cross-service data sharing.

Success Measures

Within the first three months, you will have:

• Fully ramped up on our architecture, business domain, and the specific constraints of deploying software to large enterprise client environments.
• Established yourself as the technical leader within the team, actively driving technical decisions.
• Begun mentoring team members and collaborating with product counterparts to define the integrations between the platform and the tools it hosts.

Within six months, you will have:

• Successfully led the team to deliver a prototype or initial release of the Deployment Platform that supports the core modernization toolset.
• Designed and implemented a streamlined process for platform updates that works within client security constraints.
• Established a precise rhythm of execution and served as a role model for a high-performing team.

Within 12 months, you will have:

• Become recognized as the go-to technical expert for the deployment and operations domain at MongoDB.
• Delivered a stable, production-ready platform that allows our Field Engineering teams to deploy tools without significant delays or approvals.
• Played a crucial role in helping recruiting and growing the engineering team.

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

This new team will architect the platform foundation and infrastructure that enables a "build once, run anywhere" model, ensuring our AI-powered modernisation suite operates seamlessly regardless of a client's security or network constraints. We are looking for engineers to join this high-visibility initiative, where you will solve unique distributed systems puzzles and help shape the future of how global enterprises leverage GenAI.

We are looking for an experienced software engineer who thrives on solving infrastructure constraints and building enterprise facing platforms. 

The ideal candidate is a hands-on technical leader who can architect complex distributed systems, mentor engineers, and collaborate with product teams to deliver a platform that minimizes deployment friction and meets customers’ compliance requirements.

This role can be based out of our Gurgaon office or Remotely in India.

The ideal candidate for this role will have

• 8+ years of software development and operations experience, with a focus on building platforms and distributable software infrastructure.
• 2+ years of experience leading, coaching, and mentoring a team of engineers to achieve high-impact results.
• Deep experience designing distributable applications that run in air-gapped or highly restricted network environments.
• Strong proficiency in containerization and orchestration, with the ability to design systems where the host executes containerized applications under strict security monitoring.
• Experience building Service Host architectures that provide shared routing, proxy layers, and API gateways for multiple underlying services.
• Experience managing persistent storage solutions (blob/file storage) within distributed systems.
• Understanding of security-first design, specifically regarding the execution of untrusted code, fine-grain access control, and rigorous input validation.
• Experience designing auto-update mechanisms for software that cannot directly access the public internet.
• Curiosity, a positive attitude, and a drive to continue learning.

Position Expectations

• Provide technical leadership and mentorship to a team of engineers, fostering a culture of innovation, quality, and continuous improvement.
• Drive the distributed infrastructure for the Application Modernisation Platform, ensuring it supports a self-service SaaS product model while operating within client-controlled environments.
• Lead the design and implementation of a sophisticated orchestration layer that manages authentication, telemetry, and the lifecycle of modernization tools.
• Architect a client-side application that manages developer workflows and communicates securely with hosted services.
• Solve complex "Day 2" operations challenges, such as designing interfaces to solve DevOps challenges to manage users, secrets, and updates.
• Collaborate with security and product teams to ensure the platform can execute code generation and LLM-based tasks securely, protecting both client data and MongoDB IP.
• Act as a hands-on leader, guiding the team through technical challenges related to container security, local vs. hosted logic distribution, and cross-service data sharing.

Success Measures

Within the first three months, you will have:

• Fully ramped up on our architecture, business domain, and the specific constraints of deploying software to large enterprise client environments.
• Established yourself as the technical leader within the team, actively driving technical decisions.
• Begun mentoring team members and collaborating with product counterparts to define the integrations between the platform and the tools it hosts.

Within six months, you will have:

• Successfully led the team to deliver a prototype or initial release of the Deployment Platform that supports the core modernization toolset.
• Designed and implemented a streamlined process for platform updates that works within client security constraints.
• Established a precise rhythm of execution and served as a role model for a high-performing team.

Within 12 months, you will have:

• Become recognized as the go-to technical expert for the deployment and operations domain at MongoDB.
• Delivered a stable, production-ready platform that allows our Field Engineering teams to deploy tools without significant delays or approvals.
• Played a crucial role in helping recruiting and growing the engineering team.

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

As an AI Workflow Specialist on the Trust & Safety Operations team, you will be the bridge between product, operations, and other relevant teams. You will be required to create workflows, using AI to design, prototype, and scale high‑impact automations. You will translate operational pain points into well‑designed AI workflows, partner closely with product and engineering, and build the evaluation frameworks that ensure these automations are safe, reliable, and measurable.

You Will:

• Partner with the Subject matter experts across the Support Ops and Shared service teams to understand the current gap and brainstorm on the desired solution. 
• Map and document existing workflows to identify high‑leverage automation opportunities and clearly define “current vs. future state.”
• Design AI‑augmented workflows that combine LLM agents, existing rules engines, and human review to improve speed, quality, and consistency 
• Prototype and iterate AI solutions using internal and external (accepted) tooling (e.g., Claude and other LLMs, internal agentic/AI workflow platforms, and Builder AI code intelligence) to turn workflow designs into working agents or automations.
• Define success metrics and evaluation plans (e.g., automation rate, handle time reduction, error/rollback rate, reviewer satisfaction) and build or integrate with eval pipelines to measure agent performance over time.
• Partner with product, engineering, and operations to prioritize use cases, scope requirements, and align AI workflows with product roadmaps and control/compliance expectations.
• Operationalize launches: contribute to playbooks, runbooks, and training so that operations teams can use AI agents confidently and understand when and how to intervene or escalate.
• Continuously improve workflows by monitoring performance, surfacing insights, and iterating on prompts, policies, routing, and UX to keep systems robust as volumes, abuse patterns, and regulations evolve.
• Champion safe and secure AI usage, partnering with security and compliance stakeholders to ensure AI workflows respect data handling, access controls, and regulatory constraints, especially as AI workloads increase.

You Have:

• 5+ years of experience in technical operations, data science/analytics, or product/engineering roles, with at least 2+ years working directly with workflow automation, rules engines, or tooling for operations teams.
• Demonstrated experience designing, implementing, or maintaining complex business workflows 
• Strong technical fluency: comfortable reading and writing simple scripts or code (Python or similar), working with APIs, and collaborating closely with engineers to ship workflow changes and integrations.
• Hands‑on experience with LLM‑based tools (e.g., Claude) or other AI platforms, including prompt design, evaluation, and iteration to improve quality and reliability.
• Strong analytical skills, with experience defining metrics, building dashboards or analyses, and using data to make prioritization and design decisions.
• Excellent cross‑functional communication skills; able to translate between operations, product, engineering, and finance, and to write clear specs, runbooks, and status updates.

Good To Have: 

• Experience in Trust & Safety, compliance, or risk‑sensitive workflows (e.g., safety queues, fraud, government or law enforcement requests, regulatory reporting).
• Prior work evaluating AI agents or automation quality (e.g., building eval suites, gold‑label sets, or reviewer workflows to monitor agent decisions).

Location Details: Gurugram

At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​

This is a hybrid position. You’ll divide your time between working remotely from your home and an office, so you should live within commuting distance. Hybrid teams may work in-office as much as a few times a week or as little as once a month or quarter, as decided by leadership. The hiring manager can share more about what hybrid work might look like for this team.

Join our Team

If you are passionate about machine learning and want to make a difference for millions of small businesses, join our DnAI (Data and Artificial Intelligence) team at GoDaddy as a Senior Machine Learning Scientist. You will have the opportunity to build cutting-edge machine learning models and Generative AI solutions to build intelligent software that delight our customers. You will work with highly skilled engineers in building comprehensive solutions to challenging business problems in customer experience, personalization; as well as solve technical problems in model evaluation, simulation and more.

What you'll get to do...

• Develop and implement advanced machine learning algorithms. 
• Build Intelligent Software using Large Language Models (AI Agents). 
• Design and refine ML models to enhance their performance, scalability, and robustness. 
• Assess, design and curate comprehensive evaluations for open-ended GenerativeAI problems. 
• Collaborate with cross-functional teams to integrate ML solutions within broader product and platform initiatives. 
• Drive the exploration and adoption of cutting-edge ML technologies to maintain our competitive edge in the industry. 

Your experience should include...

• 6+ years of overall experience in machine learning related roles.
• Strong knowledge of machine learning algorithms, tools, and techniques, such as supervised and unsupervised learning, deep learning, computer vision, natural language processing, etc. 
• Familiarity with AI assisted coding tools like Cursor, Claude Code or VS Code. 
• Proficient in Python programming language with familiarity with software engineering best practices, such as version control, code review, CI/CD, etc. 
• Proficiency with prompt engineering and large language models (LLM) and Natural Language Processing (NLP).

You might also have...

• Experience building conversational systems. 
• Experience in designing comprehensive evaluations and verification methods. 
• Proficiency in Typescript is a plus.

We've got your back...  We offer a range of total rewards that may include paid time off, retirement savings (e.g., 401k, pension schemes), bonus/incentive eligibility, equity grants, participation in our employee stock purchase plan, competitive health benefits, and other family-friendly benefits including parental leave. GoDaddy’s benefits vary based on individual role and location and can be reviewed in more detail during the interview process.

We also embrace our diverse culture and offer a range of Employee Resource Groups (Culture). Have a side hustle? No problem. We love entrepreneurs! Most importantly, come as you are and make your own way. 

We encourage you to apply even if your experience or skillset doesn’t align perfectly with every requirement. We value a wide range of backgrounds and transferable skills, and we are excited to support learning and growth.

About us...  GoDaddy is empowering everyday entrepreneurs around the world by providing the help and tools to succeed online, making opportunity more inclusive for all. GoDaddy is the place people come to name their idea, build a professional website, attract customers, sell their products and services, and manage their work. Our mission is to give our customers the tools, insights, and people to transform their ideas and personal initiative into success. To learn more about the company, visit About Us. 

At GoDaddy, we know diverse teams build better products—period. Our people and culture reflect and celebrate that sense of diversity and inclusion in ideas, experiences and perspectives. But we also know that’s not enough to build true equity and belonging in our communities. That’s why we prioritize integrating diversity, equity, inclusion and belonging principles into the core of how we work every day—focusing not only on our employee experience, but also our customer experience and operations. It’s the best way to serve our mission of empowering entrepreneurs everywhere, and making opportunity more inclusive for all. To read more about these commitments, as well as our representation and pay equity data, check out our Diversity and Pay Parity annual report which can be found on our Diversity Careers page.

GoDaddy is proud to be an equal opportunity employer. GoDaddy will consider for employment qualified applicants with criminal histories in a manner consistent with local and federal requirements. Refer to our full EEO policy.

Our recruiting team is available to assist you in completing your application. If they could be helpful, please reach out to myrecruiter@godaddy.com. 

GoDaddy doesn’t accept unsolicited resumes from recruiters or employment agencies.

We are seeking a highly motivated Senior Analyst, Tools and Systems Administrator to manage the implementation and innovation of tooling initiatives across our Operations teams. In this role, you will join a growing team of administrative, incident management and product support teams in India, providing comprehensive tools and admin support to our global operations teams. You will help build a premier suite of agent tooling by managing systematic changes, identifying improvements, and delivering exceptional customer service.

You Will:

• Administer and configure applications to support 24/7 operations, including Zendesk, Absorb, Qualtrics, JIRA and other 3rd party and internally developed tools.
• Analyze and translate business requirements into technical requirements, coordinating with operations teams to evaluate new functionality and implement tooling.
• Support vendor team onboarding and off-boarding, including account creation, access provisioning, and the setup and troubleshooting of provisioned tools.
• Respond to and resolve ad-hoc tickets from internal and vendor facing teams via Jira, while monitoring Slack pings, emails, and collaborating with global operational teams.
• Work proactively with internal and external teams to identify, analyze, and resolve tool-related issues before problems arise, ensuring all incident management protocols are diligently followed.
• Maintain detailed documentation and provide regular reports on configuration, experience and support activities.

You Have:

• 7+ years of experience in tools and systems administration, focusing heavily on end-user support, alongside 2+ years of experience with CRM, IVR, LMS, Knowledge Management tools, live channel support systems, integrations, and database administration.
• 2+ years of experience owning the end-to-end implementation, instrumentation, and integration of front and back-office applications.
• The ability to use data to identify and lead decision-making for process improvements that enhance operational efficiencies.
• Experience collaborating and communicating technical information clearly to management, product development teams, and both technical and non-technical users.
• Leveraged AI / LLM based tools to solve complex problems.

You Are:

• Analytical & Innovative: You are excited to investigate large, ambiguous problems, measure solutions, and execute out-of-the-box ideas to mitigate emerging risks.
• A Proactive Problem Solver: You anticipate potential problems, take decisive action to solve them autonomously, and prioritize effectively.
• Customer-Focused: You are passionate about delivering exceptional customer service and resolving issues efficiently while managing conflicting priorities for internal and external customers.
• Team-Oriented: You lift up your peers, work effectively as part of a global team, and are able to work flexible hours to adapt to changing priorities.

Position Summary

Arcesium seeks an experienced Data Scientist professional to join our Business Operations team within the Client and Partner Development (CPD) organization. The ideal candidate will be comfortable working across large volumes of varied datasets spanning pricing, headcount, market research, commercial performance, and translating that data into the models, frameworks, and insights that drive decision-making. Beyond building models and reporting on data, this person will be expected to draw principled conclusions from their analysis and present clear, strategic recommendations to senior leadership. You will also play an active role in identifying AI-driven solutions that improve how the team works and be a part of AI strategy for CPD. You will collaborate closely with global CPD teams across Sales & Partnership, Revenue Operations, Marketing, Forward Deployed, Account Management and Client Success, Service and Solutions teams to execute complex projects and help the organization scale through data-backed governance.

What you'll do:

• Identify relevant data sources and work with CPD stakeholders across functions to collect, analyze, and interpret large structured and unstructured datasets spanning domains such as pricing, headcount, market research, and operational metrics.
• Devise and apply algorithms and models to extract insight from large data stores. Conduct data and error analysis to improve model performance, and clean and validate data for uniformity and accuracy.
• Analyze data for trends and patterns with clear objectives in mind. Interpret outputs and draw principled conclusions rather than stopping at the analysis itself, ensuring findings inform real decisions.
• Implement analytical models and reporting frameworks end to end, from data ingestion through to leadership-ready outputs.
• Conduct what-if and scenario analyses and translate outputs into clear narratives that are actionable at the senior leadership level.
• Design and develop automation scripts and data pipelines to synthesize and structure data from diverse sources, applying critical thinking to move toward zero-touch processes and maximize end-to-end efficiency.
• Produce KPI dashboards and performance reports using historical data to surface trends and productivity insights for executive audiences, with a focus on telling the story behind the data.
• Act as the primary internal champion for responsible, practical AI use within CPD, educating stakeholders, setting best practices, and ensuring solutions are sustainable and governed.
• Develop reusable AI frameworks, prompt libraries, and automation components that scale adoption across the CPD organization and serve as a foundation for future capabilities.

What you'll need:

• Strong verbal and written communication skills, with the ability to present analytical findings clearly to senior leadership and stakeholders across functions.
• 4 to 7 years of experience in a data analytics or business operations role. Prior experience at a financial technology firm is a plus.
• Advanced proficiency in Excel including complex formulas and VBA Macro programming. Strong Excel fundamentals are a core expectation of this role.
• Proficiency in Python or similar scripting languages for data transformation, automation, and analysis.
• Working knowledge of SQL for querying and managing structured datasets.
• Experience with data visualization tools, particularly Power BI, to build dashboards and reports for executive and operational audiences.
• Experience with data mining and statistical analysis, including segmentation techniques and statistical packages for working with large datasets.
• Proven ability to conduct what-if and scenario analysis and communicate implications clearly to non-technical senior stakeholders.
• Experience tracking KPIs and relevant metrics for revenue organizations, aligned with broader organizational performance indicators.
• Demonstrated hands-on experience building AI-powered workflows, automation pipelines, or LLM-assisted tools in a business context.
• Genuine intellectual curiosity about AI and a track record of applying it to real operational problems.
• Ability to balance medium to long-term analytical projects alongside day-to-day operational responsibilities.

Arcesium's Personal Data Privacy Notice for Candidates is linked here. 

Role Summary

We are hiring Senior Engineers who combine solid software engineering fundamentals with proven proficiency in AI-assisted development. This role is designed for engineers who have actively used AI coding tools (such as Cursor, Claude Code, Codex CLI only) for at least one year and can leverage these capabilities to ship higher-quality code faster. You will be embedded in product engineering squads, leading feature development, mentoring junior engineers, and championing AI-first development practices across the team.

What Makes This Role Different

This is not an AI research role - it is a core engineering role for engineers who use AI as a force multiplier. We expect you to:

• Use AI coding assistants daily to accelerate development without sacrificing code quality.
• Critically evaluate AI-generated code for correctness, security vulnerabilities, and maintainability.
• Share best practices for AI-assisted workflows with the broader engineering team.
• Help define team standards for responsible and effective AI tool adoption.

Key Responsibilities

1  Feature Engineering & Delivery

• Design, build, and ship production-quality features across the full stack or within your domain (backend, frontend, platform, or data).
• Leverage AI coding assistants to write, refactor, document, and test end-to-end code efficiently.
• Translate product requirements and technical specifications into clean, maintainable implementations.
• Lead feature squads for medium-complexity initiatives from design through deployment.
• Participate in and drive sprint planning, backlog grooming, and technical estimation sessions.

2  AI-Augmented Development Practices

• Champion the use of AI pair-programming tools (Copilot, Cursor, Claude, etc.) across the engineering org.
• Develop and document internal guidelines for effective AI prompt engineering within coding workflows.
• Conduct training sessions or knowledge-share presentations on maximising productivity with AI tools.
• Critically audit AI-generated code for logic errors, security issues, and performance anti-patterns before merging.
• Stay updated on the latest AI development tooling and evaluate new tools for team adoption.

3  Code Quality & Engineering Excellence

• Write testable, modular, and well-documented code following the team's style guides and design principles.
• Drive test-driven development (TDD) and maintain code coverage targets.
• Perform thorough code reviews with constructive feedback; uphold engineering standards.
• Identify and address technical debt proactively; contribute to architecture improvements.
• Participate in RCA (root cause analysis) for production incidents; implement lasting fixes.

4  Architecture & Technical Design

• Contribute to system design discussions, proposing solutions with appropriate trade-off analysis.
• Create and maintain technical design documents (TDDs), ADRs (Architecture Decision Records), and API contracts.
• Evaluate and adopt relevant third-party libraries, APIs, and SaaS tools with a security-first mindset.
• Collaborate with platform / DevOps teams on observability, CI/CD pipelines, and infrastructure-as-code.

5  Mentoring & Team Growth

• Mentor 1–2 mid-level engineers; conduct regular 1:1 technical coaching sessions.
• Onboard new team members by sharing codebase context, tooling setup, and team practices.
• Contribute to a culture of psychological safety, learning from failures, and continuous improvement.

6  Cross-functional Collaboration

• Work closely with Product Managers, Designers, and Operations to deliver delightful, high-quality user experiences.
• Coordinate with data and AI/ML teams to integrate model endpoints, APIs, and AI features into product surfaces.
• Participate in customer-facing escalations where deep technical expertise is required.

Required Qualifications

1  Education

• Bachelor's degree in Computer Science, Software Engineering, or a related field.
• Candidates without a degree but with a strong portfolio and demonstrable project history will be considered.

2  Experience

• 3 – 5 years of professional software engineering experience in a product-focused environment.
• Minimum 1 year of active, hands-on experience using AI coding tools in professional work (not just personal projects).
• Track record of shipping production features end-to-end with measurable business impact.

3  Technical Skills — Core Engineering

• Languages: Proficiency in at least one of — Python, TypeScript/JavaScript, Java, Go, or Kotlin.
• Web / API: REST, GraphQL, gRPC; familiarity with microservices and event-driven architectures.
• Databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis, DynamoDB).
• Cloud: AWS, GCP, or Azure — compute, storage, serverless, and managed services.
• DevOps: Docker, Kubernetes, CI/CD (GitHub Actions, Jenkins, CircleCI); IaC basics (Terraform/Pulumi).
• Testing: Unit, integration, and e2e testing frameworks; TDD/BDD familiarity.
• Version Control: Git, branching strategies (GitFlow, trunk-based), PR workflows.

4  AI Tooling Skills (Mandatory)

• Demonstrated proficiency with at least one AI coding assistant (Cursor IDE, Claude Code, Codex CLI).
• Ability to craft effective prompts for code generation, refactoring, debugging, and documentation tasks.
• Experience reviewing and validating AI-generated code for correctness and security.
• Understanding of limitations of LLM-based coding tools (hallucinations, context window, license risks).

5  Nice to Have

• Contributions to open-source projects.
• Experience building or integrating AI/ML features (e.g., calling LLM APIs, embedding models, RAG pipelines).
• Familiarity with agentic coding frameworks (LangChain, LlamaIndex, AutoGen, CrewAI).
• Experience in a startup or scale-up environment with rapid iteration cycles.
• Knowledge of web security (OWASP Top 10, secure coding practices).

Behavioural Competencies

• AI-First Mindset: Naturally reaches for AI tools to accelerate tasks while maintaining engineering rigour.
• Ownership: Takes end-to-end accountability — from design to deployment to monitoring.
• Pragmatism: Balances perfect with shipped; knows when to iterate vs. over-engineer.
• Mentorship: Invests in the growth of peers and junior colleagues.
• Communication: Writes clearly (code comments, docs, Slack) and articulates trade-offs confidently.
• Curiosity: Continuously explores new tools, languages, and architectural patterns.
• Collaboration: Works well in cross-functional squads; builds trust quickly.

About the Role 

Anaplan is on a mission to revolutionize business planning by connecting organizations and people to make better, faster decisions. We are seeking a visionary Senior Manager for AI Engineering to lead our talented team in building the next generation of intelligent planning solutions. This is a critical leadership role where you will drive the technical strategy and execution for AI/ML initiatives, directly impacting Anaplan’s product and our customers' success. You will be at the forefront of integrating cutting-edge AI, from time series forecasting to generative and agentic AI, into our market-leading platform. 

Key Responsibilities 

• Lead, mentor, and grow a high-performing team of AI/ML engineers, fostering a culture of innovation, collaboration, and excellence. 

• Define and execute the roadmap for AI/ML projects, ensuring alignment with business objectives and product strategy. 

• Architect and oversee the development of scalable, robust, and production-grade AI systems on cloud platforms (AWS, Azure, GCP). 

• Drive best practices for the full machine learning lifecycle, including MLOps, CI/CD for ML, model monitoring, and governance. 

• Collaborate closely with product managers, data scientists, and other engineering leaders to translate business requirements into technical solutions. 

• Stay at the forefront of advancements in AI/ML, including Large Language Models (LLMs) and agentic AI, to identify and implement new opportunities. 

• Manage project timelines, resources, and stakeholder communication to ensure the timely delivery of high-quality AI solutions. 

Required Qualifications 

• Proven experience leading AI/ML teams in a SaaS or enterprise software environment. 

• Deep expertise in time series forecasting and machine learning. 

• Experience architecting and deploying scalable, production-grade AI systems on cloud platforms (AWS, Azure, GCP). 

• Solid understanding of MLOps, CI/CD for ML, and cloud-native architectures. 

• Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns. 

• Experience with agentic frameworks and autonomous agent architectures. 

• Proficiency in Python and modern software development practices (testing, code review, CI/CD). 

• Proven track record of delivering complex technical projects on time with high quality. 

• Excellent communication, collaboration, and stakeholder management skills. 

• Track record of delivering impactful AI solutions in a fast-paced, agile environment. 

Preferred Qualifications 

• Master’s or Ph.D. in Computer Science, AI, Machine Learning, or a related field. 

• Experience with large-scale data processing frameworks like Spark. 

• Familiarity with the challenges of applying AI in enterprise planning or financial domains. 

• A portfolio of published research or contributions to open-source AI projects. 
• 10 Years +

What Makes This Role Exciting 

You will be a key leader in Anaplan’s AI journey, with the autonomy to shape our technical direction and build a world-class engineering team. This is a unique opportunity to solve complex, real-world problems and deliver intelligent solutions that empower major global enterprises to make more informed decisions. You will work with a passionate team on the cutting edge of AI, making a tangible impact on our product and the industry. 

Role Summary

We are seeking a Lead Engineer, AI Systems to serve as the technical anchor across our AI-augmented engineering organisation. This role bridges our Senior AI Coding Engineers, the AI/ML Developer (SLM Specialist), and the Agentic Systems intern cohort. You will set technical direction, own cross-cutting architectural decisions, and champion the responsible, high-impact adoption of AI-assisted development practices across the entire engineering function.

You will remain hands-on with code while simultaneously shaping how the wider team builds, evaluates, and ships AI-powered products.

Key Responsibilities

1  Technical Vision & Architecture

• Define and own the end-to-end technical architecture for AI Systems — spanning product feature surfaces, model inference APIs, and agentic toolchains.
• Drive Architecture Decision Records (ADRs), system design reviews, and RFC processes across squads.
• Establish standards for integrating SLM/LLM model endpoints into product surfaces built by the Senior Engineering team.
• Evaluate emerging AI infrastructure patterns (RAG, agentic orchestration, vector stores, model serving) and guide adoption decisions.
• Own the technical roadmap for AI tooling, developer productivity, and model integration layers.

2  Cross-Squad Technical Leadership

• Act as the primary technical liaison between the AI/ML Developer (model side) and Senior Engineers (product side), ensuring smooth API contracts, evaluation loops, and deployment handoffs.
• Provide technical direction to Agentic Systems interns, reviewing designs, code, and agentic pipeline implementations.
• Unblock senior engineers on hard architectural or integration challenges that span squad boundaries.
• Run cross-team design reviews, architecture syncs, and engineering guild sessions.

3  AI-Augmented Engineering Excellence

• Define and maintain the organisation’s standards for AI-assisted development — covering context engineering, AI code review protocols, context management, and tool evaluation criteria.
• Maintain and evolve the internal AI tooling playbook (Cursor IDE, Claude Code, Codex CLI, and emerging tools).
• Evaluate new AI coding tools, agentic frameworks (LangChain, LlamaIndex, CrewAI, AutoGen), and developer-productivity platforms; produce adoption recommendations with measured trade-offs.
• Conduct structured audits of AI-generated code across squads for correctness, security, and maintainability.

4  Hands-On Engineering

• Remain an active contributor: own critical-path features, prototype architectural spikes, and build shared infrastructure components used across squads.
• Personally drive resolution of the most complex production incidents and root-cause analyses.
• Review and merge high-impact PRs; maintain the highest code review quality bar on the team.
• Own observability and reliability for AI inference and MLOps integration layers in production.

5  Mentoring & Talent Development

• Mentor Senior Engineers, the AI/ML Developer, and interns through technical coaching, design feedback, and stretch assignments.
• Lead hiring panels and technical interviews; help define and uphold the engineering hiring bar.
• Contribute to onboarding frameworks that embed AI-first practices from day one.
• Model a culture of rigorous experimentation, psychological safety, and continuous improvement.

6  Stakeholder & Product Collaboration

• Partner with the Director of Engineering and Product leadership to translate product strategy into a phased technical roadmap.
• Present architectural proposals and trade-off analyses to engineering leadership and executive stakeholders as required.
• Coordinate with DevOps/Platform teams on GPU/TPU compute provisioning, CI/CD for model pipelines, and cloud cost optimisation.

Required Qualifications

1  Education

• Bachelor’s or Master’s degree in Computer Science, or a related field.
• Candidates without a degree but with a compelling portfolio demonstrating scope and impact at staff/lead level will be considered.

2  Experience

• 6 – 8 years of professional software engineering experience in product-focused environments.
• Minimum 2 years in a formal or de-facto technical lead / staff engineer capacity across multiple squads or systems.
• Minimum 8-12 months of active, hands-on experience with AI coding tools in a professional engineering setting.
• Proven track record of shipping production systems with measurable business impact at scale.
• Demonstrated experience collaborating closely with ML/AI model teams on integration, deployment, and evaluation.

3  Technical Skills — Core Engineering

• Languages: Expert proficiency in at least two of — Python, TypeScript/JavaScript, Go.
• Architecture: Microservices, event-driven systems, API design (REST, GraphQL, gRPC), distributed systems fundamentals.
• Databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis); vector databases (FAISS, Pinecone, Weaviate).
• Cloud: AWS, GCP, or Azure — compute, storage, serverless, managed ML services (SageMaker, Vertex AI).
• DevOps: Docker, Kubernetes, CI/CD (GitHub Actions, Jenkins); IaC (Terraform/Pulumi); observability stacks.
• Testing: TDD/BDD; unit, integration, and e2e frameworks; model evaluation pipelines.

4  AI / ML Integration Skills (Mandatory)

• Demonstrated proficiency with AI coding assistants (Cursor IDE, Claude Code, Codex CLI) in daily professional workflows.
• Experience designing and consuming LLM/SLM inference APIs; understanding of model serving, latency, and cost trade-offs.
• Hands-on familiarity with RAG architectures, vector stores, and retrieval pipelines.
• Ability to define and enforce AI code quality standards across an engineering team.
• Understanding of LLM limitations: hallucinations, context window constraints, prompt injection risks, and licensing considerations.

5  Technical Skills — Nice to Have

• Experience with SLM/LLM training or fine-tuning pipelines (SFT, RLHF, LoRA/QLoRA).
• Familiarity with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI) and multi-step reasoning pipelines.
• Contributions to open-source ML or developer tooling projects.
• Knowledge of OWASP Top 10, secure coding, and AI-specific security risks (prompt injection, model exfiltration).
• Prior experience in a high-growth startup or scale-up environment with rapid iteration cycles.

Behavioural Competencies

• AI-First Mindset: Defaults to AI tools to accelerate work while maintaining rigorous quality standards; actively pushes the team’s AI capability forward.
• Systems Thinking: Sees the full picture — how model outputs, product surfaces, and infrastructure interdepend; anticipates second-order effects of architectural choices.
• Ownership: Takes end-to-end responsibility from design through production; doesn’t hand off problems, solves them.
• Influence Without Authority: Earns trust through technical credibility; drives alignment through persuasion, data, and well-reasoned proposals.
• Communication: Writes clear design docs, ADRs, and post-mortems; articulates complex trade-offs for engineering peers and non-technical stakeholders.
• Mentorship: Actively invests in the growth of engineers at all levels; gives direct, constructive feedback.
• Pragmatism: Balances the ideal with the shipped; knows when to iterate vs. refactor vs. rewrite.
• Curiosity: Continuously explores emerging research, tools, and patterns — and brings those learnings back to the team.

Role Summary

We are looking for a technically strong AI / ML Developer with hands-on expertise in training and fine-tuning Small Language Models (SLMs) and RAG Solutions. The ideal candidate will drive end-to-end AI Solutions — from dataset curation and pre-processing to training, evaluation, and production deployment. You will collaborate closely with product, product engineers, and infrastructure teams to build AI solutions that are efficient, scalable, and business-aligned.

Key Responsibilities

1  Model Design & Training

• Design, train, and fine-tune Small Language Models (SLMs) using frameworks such as PyTorch, TensorFlow, or JAX.
• Conduct experiments with supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuning.
• Implement efficient training pipelines leveraging distributed training (DDP, FSDP) across GPU/TPU clusters.
• Perform hyperparameter optimisation, ablation studies, and model selection based on benchmark results.
• Develop and maintain data pipelines for collecting, cleaning, tokenising, and pre-processing large-scale training corpora.

2  Model Evaluation & Quality

• Define and implement evaluation frameworks including perplexity, BLEU, ROUGE, BERTScore, and task-specific benchmarks.
• Conduct red-teaming, bias analysis, and safety evaluations to ensure responsible AI deployment.
• Benchmark models against established baselines (e.g., GPT-2, Phi, Mistral) and track performance over iterations.
• Collaborate with QA teams to build regression suites for model versioning and continuous evaluation.

3  MLOps & Deployment

• Containerise and deploy models using Docker, Kubernetes, and cloud-native ML platforms (AWS SageMaker / GCP Vertex AI / Azure ML).
• Build and maintain model registries, experiment tracking (MLflow, Comet), and reproducible training pipelines.
• Optimise inference performance through quantisation (INT8, INT4), pruning, distillation, and ONNX/TensorRT conversion.
• Monitor model drift, data drift, and performance degradation in production; implement automated retraining triggers.

4  Research & Innovation

• Stay current with state-of-the-art NLP/LLM research; prototype and validate new techniques from published literature.
• Contribute to internal knowledge sharing, technical documentation, and model cards.
• Explore parameter-efficient fine-tuning (PEFT) methods such as LoRA, QLoRA, and Adapter layers.
• Investigate and apply mixture-of-experts (MoE), retrieval-augmented generation (RAG), and agentic workflows as needed.

5  Collaboration & Stakeholder Management

• Work with product managers and domain experts to translate business requirements into model objectives and KPIs.
• Communicate model capabilities, limitations, and trade-offs clearly to both technical and non-technical stakeholders.
• Participate in architecture reviews, sprint planning, and cross-functional design discussions.

Required Qualifications

1  Education

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, or a related quantitative field.
• Equivalent professional experience with a strong portfolio of delivered AI/ML projects will be considered.

2  Experience

• 4 – 6 years of professional experience in machine learning or NLP engineering.
• Minimum 2 years of direct, hands-on experience in training or fine-tuning language models (LLMs or SLMs).
• Demonstrable experience taking a model from dataset preparation through to production deployment.

3  Technical Skills — Core

• Programming: Python (proficient); familiarity with C++/CUDA a plus.
• Deep Learning Frameworks: PyTorch (primary), TensorFlow or JAX.
• NLP Libraries: Hugging Face Transformers, Datasets, PEFT, TRL, Accelerate.
• Training Infrastructure: Multi-GPU training, FSDP, DeepSpeed ZeRO stages 1–3.
• Data Engineering: Pandas, NumPy, Apache Spark or Dask for large-scale data prep.
• Vector DBs & Retrieval: FAISS, Pinecone, Weaviate, or equivalent.
• Cloud Platforms: AWS, GCP, or Azure — ML-specific services (SageMaker, Vertex AI, etc.).
• Version Control & CI/CD: Git, GitHub/GitLab, MLflow or W&B for experiment tracking.

4  Technical Skills — Nice to Have

• Experience with multimodal models or vision-language models (VLMs).
• Knowledge of model safety, alignment techniques, and responsible AI frameworks.
• Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks.
• Contributions to open-source ML projects or publications at NeurIPS, ICML, EMNLP, ACL.

Behavioural Competencies

• Intellectual Curiosity: Keeps up with rapidly evolving AI research and applies learnings pragmatically.
• Problem Solving: Approaches ambiguous problems with structured, data-driven thinking.
• Ownership: Takes full accountability for model quality, timelines, and production reliability.
• Collaboration: Works effectively in cross-functional teams with diverse skill sets.
• Communication: Distils complex technical concepts for diverse audiences.
• Adaptability: Thrives in a fast-paced environment where priorities evolve with research breakthroughs.

Job Title: Senior Full Stack Machine Learning Engineer

About Us:

Inovalon is a leading healthcare technology company dedicated to revolutionizing the healthcare industry through innovative AI and machine learning solutions. Our mission is to leverage cutting-edge technology to improve health outcomes and streamline healthcare processes. We are looking for a talented and experienced Senior Full Stack Machine Learning Engineer to join our dynamic team.

Job Description:

• As a Senior Full Stack Machine Learning Engineer, you will play a pivotal role in designing, developing, and deploying machine learning models that drive our healthcare solutions. You will work closely with data scientists, software engineers, and product managers to build scalable and robust machine learning systems. Your expertise will help us transform healthcare data into actionable insights, ultimately improving patient care and operational efficiency.

Key Responsibilities:

• Model Development: Design, implement, and optimize machine learning models for various healthcare applications, including predictive analytics, natural language processing, and generative AI.
• End-to-End Deployment: Develop and maintain the full lifecycle of machine learning solutions, from data preprocessing and model training to deployment and monitoring in production environments.
• Data Engineering: Collaborate with data engineers to build and maintain data pipelines, ensuring the availability of high-quality data for training and inference.
• Software Development: Write clean, efficient, and maintainable code for machine learning applications, ensuring seamless integration with existing systems.
• Performance Optimization: Continuously monitor and improve the performance of machine learning models and systems, addressing issues related to scalability, latency, and accuracy.
• Collaboration: Work closely with cross-functional teams to understand business requirements and translate them into technical solutions.
• Mentorship: Provide guidance and mentorship to junior engineers, fostering a culture of continuous learning and innovation.

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
• Experience: Minimum of 5 years of experience in machine learning, with a proven track record of deploying models in production environments.

Technical Skills:

• Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Proficiency in building applications leveraging generative AI technologies which includes LLM’s, prompt engineering, Vector Databases, RAG architectures and transfer learning is a plus.
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes).
• Strong knowledge of data structures, algorithms, and software engineering best practices.
• Familiarity with big data technologies (e.g., Hadoop, Spark) and data pipeline tools (e.g., Airflow, Kafka).
• Experience with frontend and backend development, including frameworks such as React, Node.js, and Django.

Domain Knowledge: Understanding of healthcare data standards (e.g., HL7, FHIR) and regulations (e.g., HIPAA) is a plus.

Soft Skills:

• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
• Ability to work independently and as part of a team in a fast-paced environment.

What We Offer:

• Competitive salary and benefits package.
• Opportunity to work on impactful projects that improve healthcare outcomes.
• Collaborative and innovative work environment.
• Professional development and growth opportunities.
• Flexible work arrangements, including hybrid and remote options.

Join us in our mission to transform healthcare through technology! We look forward to hearing from you.

Job Description

PayPay India growth is driving a rapid expansion of PayPay India product teams and the need for a Senior Technical Program Manager to drive more features to deliver and accelerate further growth. PayPay India Private Limited applies different SDLC methodologies to develop our products, continuously tailoring them, aligning the company's strategies to pursue the speed. 

A successful candidate will drive the product team's product workup and delivery, as well as foster the advanced agile culture that fits PayPay India  speed and scale of the company by establishing a new better PayPay product delivery life cycle.

Main Responsibilities 

• Foster Agile methodologies, principles, and practices within the teams. 
• Develop and tailor the PayPay SDLC framework aligned with industry Agile best practices and PayPay's strategies. 
• Plan and cultivate Agile maturity at the team level and scale it to the divisional level. 
• Manage multiple technical projects concurrently, ensuring timely delivery and superior outcomes. 
• Monitor the status of the development project, including progress, issues, timelines, and risks. Communicate transparently with stakeholders. 
• Coordinate and facilitate daily/weekly meetings with stakeholders. 
• Cultivate a collaborative environment that promotes visibility and transparency among teams. 
• Provide support in maintaining task management software.

Minimum Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. 
• 10+ years of relevant work experience, including 7+ years in a senior technical program management role. 
• Proven experience leading complex technical projects, driving organizational transformation initiatives (such as Agile adoption), and applying Agile methodologies (Scrum, Kanban, etc.). 
• Proven leadership in large-scale programs or managing multiple complex projects simultaneously. 
• Demonstrated success in leading large-scale programs or managing multiple complex projects simultaneously, with a focus on strategic planning and driving organizational goals. 
• Strong analytical and problem-solving skills, with the ability to gather data, identify risks, and develop solutions. 
• Experience in project planning, resource allocation, risk management, and budgeting. 
• Excellent written and verbal communication skills to effectively interact with technical and non-technical stakeholders at all levels. 
• Strong interpersonal skills to build relationships, facilitate discussions, and manage teams.

Preferred Qualifications

• Technical adaptability with knowledge of programming languages, platforms, and technologies relevant to the organization. 
• Proficiency in using program management tools (Jira, Confluence, etc.) to streamline project execution. 
• Experience in the FinTech industry, with knowledge of financial systems, regulations, and security standards. 
• Business-level English fluency for effective collaboration in a dynamic environment.
• Agile Expertise Certification in Agile methodologies (CSM, SAFe, PMI-ACP, etc.), demonstrating commitment to continuous improvement and team-based delivery models. 
• Strong interest in Pay2 DC Culture
• Leverage AI/LLM-based tools in daily workflows (e.g., code development, reviews, testing, debugging, documentation), while ensuring human oversight, judgment, and            accountability drive the final product.
• [Extra requirements depending on the potential team it has been identified]

Remarks

＊Please note that you cannot apply for PayPay (Japan-based jobs) or other positions in parallel or in duplicate.

PayPay 5 senses

• Please refer PayPay 5 senses to learn what we value at work.

Working Conditions 

Employment Status

• Full Time

Office Location

• Gurugram (Wework)

     ※The development center requires you to work in the Gurugram office to establish the strong core team.
     　

About Turing:

Based in Palo Alto, California, Turing is one of the world's fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. Turing helps customers in two ways: working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior , multimodality, multilingualism, STEM and frontier knowledge; and leveraging that expertise to build real-world AI systems that solve mission-critical priorities for Fortune 500 companies and government institutions. Turing has received numerous awards, including Forbes's "One of America's Best Startup Employers," #1 on The Information's annual list of "Most Promising B2B Companies," and Fast Company's annual list of the "World's Most Innovative Companies." Turing's leadership team includes AI technologists from industry giants Meta, Google, Microsoft, Apple, Amazon, Twitter, McKinsey, Bain, Stanford, Caltech, and MIT. For more information on Turing, visit www.turing.com. For information on upcoming Turing AGI Icons events, visit go.turing.com/agi-icons.

About the role: 

Turing is looking for people with GenAI experience to join us in solving business problems for our Fortune 500 customers. You will be a key member of the Turing Intelligence delivery organization and part of  a GenAI project. You will be required to lead a team of other Turing engineers across different skill sets. In the past, the Turing GenAI delivery organization has implemented industry leading multi-agent LLM systems and LLM deployments for major enterprises. 

Required skills:

• 12+ years of professional experience in software engineers and building applications/systems
• 2+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques particularly multi-agent systems. 
• Expert proficiency in programming skills in Python, Langgraph and SQL is a must.
• Expert in architecting GenAI applications/systems using various frameworks & cloud services
• Expert proficiency in using AI tools like claude code, codex, cursor, windsurf and the likes. 
• Expert proficiency in AI observability & evaluation tools like Langsmith, Langfuse or similar
• Good proficiency in using various cloud services from Azure, GCP, or AWS for building the GenAI applications
• Experience in driving the engineering team toward a technical roadmap.
• Excellent communication skills to effectively collaborate with business SMEs

Roles & Responsibilities:

• Solutioning & Lead
• Build the technical roadmap given a business requirement and own the delivery of the same.
• Lead the engineering team toward a technical roadmap and ensure timely execution of the roadmap to achieve customer satisfaction. 
• Design robust multi-agent architectures including supervisor-router patterns with dynamic sub-agent routing and stopping conditions
• Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.
• Hands-on skills
• Develop LLM-based solutions: Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like retrieval-augmented generation (RAG) and multi-agent based architectures.
• Build and maintain agent evaluation pipelines, including offline eval datasets, LLM-as-judge, and CI-integrated eval runs
• Codebase ownership: Build & maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
• Cloud integration: Deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
• Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.

About the role: 

Turing is looking for people with LLM experience to join us in solving business problems for our Fortune 500 customers. You will be a key member of the Turing GenAI delivery organization and part of  a GenAI project. You will be required to work with a team of other Turing engineers across different skill sets. In the past, the Turing GenAI delivery organization has implemented industry leading multi-agent LLM systems, RAG systems, and Open Source LLM deployments for major enterprises. 

Roles & Responsibilities:

• Develop and optimize LLM-based solutions: Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
• Codebase ownership: Maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
• Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
• Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
• Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.
• Continuous innovation: Stay abreast of the latest advancements in LLM research and generative AI, proposing and experimenting with emerging techniques to drive ongoing improvements in model performance.

Required skills:

• 8+ years of professional experience in building Machine Learning models & systems
• 1+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques particularly prompt engineering, RAG, and agents.
• Experience in driving the engineering team toward a technical roadmap.
• Expert proficiency in programming skills in Python, Langchain/Langgraph and SQL is a must.
• Understanding of Cloud services, including Azure, GCP, or AWS
• Excellent communication skills to effectively collaborate with business SMEs

About the role: 

Turing is looking for people with LLM experience to join us in solving business problems for our Fortune 500 customers. You will be a key member of the Turing GenAI delivery organization and part of a GenAI project. You will be required to work with a team of other Turing engineers across different skill sets. In the past, the Turing GenAI delivery organization has implemented industry leading multi-agent LLM systems, RAG systems, and Open Source LLM deployments for major enterprises. 

Required skills

• 8 + years of professional, hands-on engineering experience, including 4–6+ years specializing in building and deploying AI/ML models and systems.
• 1+ year of experience in developing Generative AI (LLM) applications using techniques like prompt engineering, RAG, and/or agents.
• Expert in architecting GenAI applications/systems using various frameworks & cloud services
• Good proficiency in using various cloud services from Azure, GCP, or AWS for building the GenAI applications
• Expert proficiency in programming skills in Python, Langchain/Langgraph and SQL is a must.
• Experience in driving the engineering team toward a technical roadmap.
• Excellent communication skills to effectively collaborate with business SMEs

Roles & Responsibilities

• Build the technical roadmap given a business requirement and own the delivery of the same.
• Lead the engineering team toward a technical roadmap and ensure timely execution of the roadmap to achieve customer satisfaction. 
• Develop and optimize LLM-based solutions: Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
• Codebase ownership: Maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
• Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
• Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
• Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.
• Continuous innovation: Stay abreast of the latest advancements in LLM research and generative AI, proposing and experimenting with emerging techniques to drive ongoing improvements in model performance.

Education

• Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, or a related technical field.

About the Role

We're seeking a versatile GenAI Software Engineer who can work across the full stack of GenAI applications, from model integration and prompt engineering to building intuitive user interfaces. You'll build production-ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills.

Key Responsibilities

• Develop end-to-end GenAI features including backend API services, model integration, model monitoring, evaluations and deployments
• Integrate and optimize LLMs for specific use cases in business planning, including prompt engineering, RAG implementation
• Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language
• Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics
• Design and develop APIs that expose AI capabilities to Anaplan's platform and third-party integrations
• Optimize model inference pipelines for performance, cost, and scalability in production environments
• Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour
• Collaborate with data scientists to productionize ML models and forecasting algorithms
• Write comprehensive tests including unit tests, integration tests, and prompt regression suites
• Participate in code reviews, technical design discussions, and knowledge-sharing sessions
• Stay current with GenAI research and tools, evaluating new models and techniques for potential adoption

Required Qualifications

• 3+ years of software engineering experience with 2+ years of understanding on ML/AI systems.
• Strong programming skills in Python including understanding of ML frameworks (PyTorch, TensorFlow, Transformers)
• Understanding or experience of building and deploying LLM-powered applications in production
• Understanding or experience of front-end development with React, TypeScript, and modern web technologies
• Understanding of RESTful API design, microservices architecture, and cloud infrastructure
• Experience with prompt engineering, RAG systems
• Understanding of ML fundamentals including NLP, time-series analysis, or recommender systems
• Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines
• Excellent problem-solving skills and attention to detail
• Bachelor’s degree in computer science, Machine Learning, or related field

Preferred Qualifications

• Experience with GenAI frameworks (LangChain, LlamaIndex, Haystack, or similar)
• Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models
• Experience with model serving frameworks (vLLM, TensorRT, Ray)
• Background in forecasting, planning, or analytics applications
• Familiarity with Anaplan or similar enterprise planning platforms
• Experience with A/B testing and experimentation frameworks for AI features
• Contributions to open-source ML projects or research publications
• Experience with model observability tools (LangSmith, W&B, MLflow)

What Makes This Role Exciting

• Lead a greenfield team building transformative AI capabilities from the ground up
• Work on cutting-edge conversational and agentic AI technologies
• Build user-facing AI features that directly impact how businesses plan and make decisions
• Experiment with the latest GenAI models and techniques
• Collaborate with talented engineers, data scientists, and product designers
• Solve unique challenges at the intersection of AI and enterprise software
• Grow your skills in both ML engineering and full-stack development

About the Role 

Anaplan is on a mission to revolutionize business planning by connecting organizations and people to make better, faster decisions. We are seeking a visionary Senior Manager for AI Engineering to lead our talented team in building the next generation of intelligent planning solutions. This is a critical leadership role where you will drive the technical strategy and execution for AI/ML initiatives, directly impacting Anaplan’s product and our customers' success. You will be at the forefront of integrating cutting-edge AI, from time series forecasting to generative and agentic AI, into our market-leading platform. 

Key Responsibilities 

• Lead, mentor, and grow a high-performing team of AI/ML engineers, fostering a culture of innovation, collaboration, and excellence. 

• Define and execute the roadmap for AI/ML projects, ensuring alignment with business objectives and product strategy. 

• Architect and oversee the development of scalable, robust, and production-grade AI systems on cloud platforms (AWS, Azure, GCP). 

• Drive best practices for the full machine learning lifecycle, including MLOps, CI/CD for ML, model monitoring, and governance. 

• Collaborate closely with product managers, data scientists, and other engineering leaders to translate business requirements into technical solutions. 

• Stay at the forefront of advancements in AI/ML, including Large Language Models (LLMs) and agentic AI, to identify and implement new opportunities. 

• Manage project timelines, resources, and stakeholder communication to ensure the timely delivery of high-quality AI solutions. 

Required Qualifications 

• Proven experience leading AI/ML teams in a SaaS or enterprise software environment. 

• Deep expertise in time series forecasting and machine learning. 

• Experience architecting and deploying scalable, production-grade AI systems on cloud platforms (AWS, Azure, GCP). 

• Solid understanding of MLOps, CI/CD for ML, and cloud-native architectures. 

• Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns. 

• Experience with agentic frameworks and autonomous agent architectures. 

• Proficiency in Python and modern software development practices (testing, code review, CI/CD). 

• Proven track record of delivering complex technical projects on time with high quality. 

• Excellent communication, collaboration, and stakeholder management skills. 

• Track record of delivering impactful AI solutions in a fast-paced, agile environment. 

Preferred Qualifications 

• Master’s or Ph.D. in Computer Science, AI, Machine Learning, or a related field. 

• Experience with large-scale data processing frameworks like Spark. 

• Familiarity with the challenges of applying AI in enterprise planning or financial domains. 

• A portfolio of published research or contributions to open-source AI projects. 
• Experience requrired - 15+ Yrears

What Makes This Role Exciting 

You will be a key leader in Anaplan’s AI journey, with the autonomy to shape our technical direction and build a world-class engineering team. This is a unique opportunity to solve complex, real-world problems and deliver intelligent solutions that empower major global enterprises to make more informed decisions. You will work with a passionate team on the cutting edge of AI, making a tangible impact on our product and the industry. 

About the Role

We're pioneering a new role focused exclusively on quality assurance for GenAI systems. As our AI QA Engineer, you'll develop testing strategies, evaluation frameworks, and quality metrics specifically designed for LLM-powered applications. This role requires a unique blend of QA expertise, understanding of GenAI behaviour, and automation skills

to ensure our AI features are reliable, accurate, and trustworthy

Key Responsibilities

• Design and implement comprehensive testing strategies for GenAI features including conversational AI, agentic systems, and LLM-powered workflows
• Develop automated test suites for prompt testing, including regression tests that detect unintended changes in model behaviour
• Create evaluation frameworks to measure GenAI quality across multiple dimensions (accuracy, relevance, safety, consistency, latency)
• Build and maintain test datasets and golden examples that represent diverse user scenarios and edge cases
• Implement monitoring and alerting systems to detect quality degradation in production GenAI features
• Perform adversarial testing to identify potential failures, hallucinations, biases, or security vulnerabilities in AI systems
• Collaborate with engineers to define acceptance criteria and quality gates for AI feature releases
• Develop tools and frameworks that make it easy for engineers to test their GenAI implementations
• Conduct user acceptance testing and gather feedback on AI feature performance from internal users
• Document testing procedures, known issues, and quality metrics in clear, accessible formats
• Partner with Product and Design teams to ensure AI features meet user experience standards
• Stay current with GenAI testing methodologies, tools, and industry best practices

Required Qualifications

• 3+ years of QA or test engineering experience, preferably with AI/ML systems.
• Strong understanding of GenAI technologies including LLMs, prompt engineering, and AI application patterns
• Experience with test automation frameworks and scripting (Python, JavaScript, Selenium, Pytest)
• Knowledge of software testing methodologies (functional, integration, regression, performance, security testing)
• Ability to design test cases and evaluation criteria for non-deterministic systems
• Strong analytical and problem-solving skills with attention to detail
• Experience with API testing tools (Postman, REST Assured) and backend testing
• Familiarity with CI/CD pipelines and automated testing integration
• Excellent communication skills for documenting issues and collaboration

Preferred Qualifications

• Experience testing conversational AI, chatbots, or agentic systems
• Knowledge of ML model evaluation metrics and techniques
• Familiarity with LLM evaluation frameworks (LangSmith, PromptFoo, Ragas)
• Experience with performance testing and load testing AI APIs
• Understanding of responsible AI principles including fairness, transparency, and safety testing
• Background in enterprise software or SaaS QA
• Experience with test management tools (TestRail, Zephyr, Jira)
• Knowledge of security testing methodologies for AI systems
• Scripting experience with Python, including working with LLM APIs

What Makes This Role Exciting

• Define QA practices for GenAI applications
• Work on cutting-edge AI technologies and help ensure they're reliable and trustworthy
• Shape quality standards that will impact millions of enterprise users
• Collaborate closely with engineers, data scientists, and product teams
• Grow expertise in a highly specialized and increasingly important domain
• Influence the entire AI product development lifecycle from design to release
• Join a team that values quality as a first-class concern, not an afterthought

About the Role 

Anaplan is on a mission to revolutionize business planning by connecting organizations and people to make better, faster decisions. We are seeking a visionary Senior Manager for AI Engineering to lead our talented team in building the next generation of intelligent planning solutions. This is a critical leadership role where you will drive the technical strategy and execution for AI/ML initiatives, directly impacting Anaplan’s product and our customers' success. You will be at the forefront of integrating cutting-edge AI, from time series forecasting to generative and agentic AI, into our market-leading platform. 

Key Responsibilities 

• Lead, mentor, and grow a high-performing team of AI/ML engineers, fostering a culture of innovation, collaboration, and excellence. 

• Define and execute the roadmap for AI/ML projects, ensuring alignment with business objectives and product strategy. 

• Architect and oversee the development of scalable, robust, and production-grade AI systems on cloud platforms (AWS, Azure, GCP). 

• Drive best practices for the full machine learning lifecycle, including MLOps, CI/CD for ML, model monitoring, and governance. 

• Collaborate closely with product managers, data scientists, and other engineering leaders to translate business requirements into technical solutions. 

• Stay at the forefront of advancements in AI/ML, including Large Language Models (LLMs) and agentic AI, to identify and implement new opportunities. 

• Manage project timelines, resources, and stakeholder communication to ensure the timely delivery of high-quality AI solutions. 

Required Qualifications 

• Proven experience leading AI/ML teams in a SaaS or enterprise software environment. 

• Deep expertise in time series forecasting and machine learning. 

• Experience architecting and deploying scalable, production-grade AI systems on cloud platforms (AWS, Azure, GCP). 

• Solid understanding of MLOps, CI/CD for ML, and cloud-native architectures. 

• Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns. 

• Experience with agentic frameworks and autonomous agent architectures. 

• Proficiency in Python and modern software development practices (testing, code review, CI/CD). 

• Proven track record of delivering complex technical projects on time with high quality. 

• Excellent communication, collaboration, and stakeholder management skills. 

• Track record of delivering impactful AI solutions in a fast-paced, agile environment. 

Preferred Qualifications 

• Master’s or Ph.D. in Computer Science, AI, Machine Learning, or a related field. 

• Experience with large-scale data processing frameworks like Spark. 

• Familiarity with the challenges of applying AI in enterprise planning or financial domains. 

• A portfolio of published research or contributions to open-source AI projects. 
• Experience - 15+ years

What Makes This Role Exciting 

You will be a key leader in Anaplan’s AI journey, with the autonomy to shape our technical direction and build a world-class engineering team. This is a unique opportunity to solve complex, real-world problems and deliver intelligent solutions that empower major global enterprises to make more informed decisions. You will work with a passionate team on the cutting edge of AI, making a tangible impact on our product and the industry. 

About the Role

We're seeking a versatile GenAI Software Engineer who can work across the full stack of GenAI applications, from model integration and prompt engineering to building intuitive user interfaces. You'll build production-ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills.

Key Responsibilities

• Develop end-to-end GenAI features including backend API services, model integration, model monitoring, evaluations and deployments
• Integrate and optimize LLMs for specific use cases in business planning, including prompt engineering, RAG implementation
• Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language
• Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics
• Design and develop APIs that expose AI capabilities to Anaplan's platform and third-party integrations
• Optimize model inference pipelines for performance, cost, and scalability in production environments
• Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour
• Collaborate with data scientists to productionize ML models and forecasting algorithms
• Write comprehensive tests including unit tests, integration tests, and prompt regression suites
• Participate in code reviews, technical design discussions, and knowledge-sharing sessions
• Stay current with GenAI research and tools, evaluating new models and techniques for potential adoption

Required Qualifications

• 3+ years of software engineering experience with 2+ years of understanding on ML/AI systems.
• Strong programming skills in Python including understanding of ML frameworks (PyTorch, TensorFlow, Transformers)
• Understanding or experience of building and deploying LLM-powered applications in production
• Understanding or experience of front-end development with React, TypeScript, and modern web technologies
• Understanding of RESTful API design, microservices architecture, and cloud infrastructure
• Experience with prompt engineering, RAG systems
• Understanding of ML fundamentals including NLP, time-series analysis, or recommender systems
• Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines
• Excellent problem-solving skills and attention to detail
• Bachelor’s degree in computer science, Machine Learning, or related field

Preferred Qualifications

• Experience with GenAI frameworks (LangChain, LlamaIndex, Haystack, or similar)
• Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models
• Experience with model serving frameworks (vLLM, TensorRT, Ray)
• Background in forecasting, planning, or analytics applications
• Familiarity with Anaplan or similar enterprise planning platforms
• Experience with A/B testing and experimentation frameworks for AI features
• Contributions to open-source ML projects or research publications
• Experience with model observability tools (LangSmith, W&B, MLflow)

What Makes This Role Exciting

• Lead a greenfield team building transformative AI capabilities from the ground up
• Work on cutting-edge conversational and agentic AI technologies
• Build user-facing AI features that directly impact how businesses plan and make decisions
• Experiment with the latest GenAI models and techniques
• Collaborate with talented engineers, data scientists, and product designers
• Solve unique challenges at the intersection of AI and enterprise software
• Grow your skills in both ML engineering and full-stack development

Job Description

 PayPay is looking for a Frontend Engineer to build and scale UI/Product experiences for our web applications. You’ll work closely with Product, Design, and Backend teams to deliver high-quality features, contribute to a growing design system.

Primary Responsibilities

• Deliver product features end-to-end: translate requirements into clean, scalable UI implementations with well-structured components and predictable data flow.
• Build reusable UI components and patterns: contribute to and extend our design system using tools like Storybook; prioritize consistency, accessibility basics, and developer ergonomics.
• Integrate APIs and handle real-world states: implement robust data fetching patterns (pagination, caching, retries), and manage loading/error/empty states with clear UX behavior.
• Write maintainable, modular code: apply good separation of concerns (presentation vs business logic vs API layer), meaningful abstractions, and clear naming; keep codebase easy to extend.
• Optimize performance and reliability: identify bottlenecks (rendering, network, bundle size), apply pragmatic improvements (memoization, debouncing, virtualization where relevant), and avoid async pitfalls (stale responses, race conditions).
• Improve engineering quality: participate actively in code reviews, raise the bar on standards, and help enforce best practices around testing strategy, i18n, and build tooling.
• Collaborate cross-functionally: work closely with PM/Design/Backend to clarify requirements, propose tradeoffs, and deliver iteratively with high ownership.
• Support operational excellence: use observability tooling (e.g., Sentry, New Relic, Kibana) to debug production issues, measure impact, and improve stability.
• Grow toward full-stack ownership (optional path): partner with backend teams and gradually take on BFF/API contributions using Node.js (NestJS/Express) as needed.

Tech Stack

Frontend: Typescript/Javascript , React/Vue, single-spa, Webpack, Jest, Storybook, i18n , micro-frontend

Middlewear : NestJS, Express

Infra/CI: AWS, Docker, Kubernetes, ArgoCD, Terraform, GitHub Actions, Jenkins

Obs/Analytics: Sentry, Kibana, New Relic, Google Analytics, Firebase

Qualifications

• 3 - 5 years of professional frontend development experience.
• Strong JavaScript fundamentals.
• Solid experience in React and/or Vue.
• Proven ability to write readable, modular, production-quality code.
• Strong problem-solving skills with practical DSA (web-relevant) comfortable reasoning about time/space complexity.
• Performance awareness: can identify bottlenecks and implement pragmatic optimizations.
• Ability to do low-level design (LLD) for frontend features: break down requirements into components/modules, define interfaces, and plan implementation in milestones.
• Good communication: can explain approach and tradeoffs clearly.
• Leverage AI/LLM based tools in daily workflows

Preferred Qualifications

• Experience with Nest.js (routing, SSR/CSR tradeoffs, data fetching strategies).
• Experience with Node.js or API integration patterns (REST, pagination, auth flows, error handling).
• Familiarity with design systems, accessibility basics, and responsive UI patterns.
• Exposure to frontend observability (error logging, basic performance metrics).
• Experience with micro-frontends (e.g., single-spa) or large-scale frontend architectures.

What success looks like

• You can independently deliver a feature end-to-end with clean architecture and reliable async handling.
• Your code is modular, maintainable, and performance-conscious.
• You contribute to consistent UI patterns and raise team quality through reviews and collaboration.

Remarks

＊Please note that you cannot apply for PayPay (Japan-based jobs) or other positions in parallel or in duplicate.

PayPay 5 senses

• Please refer PayPay 5 senses to learn what we value at work.

Working Conditions 

Employment Status

• Full Time

Office Location

• Gurugram (Wework)

　　※The development center requires you to work in the Gurugram office to establish the strong core team.
　　　

Role Summary

We’re looking for a Principal Architect who is a tech enthusiast with a drive for excellence and an out-of-the-box mindset to satisfy business needs in a complex payments environment. You will be a key technical leader in our Cloud Modernization initiative while also accelerating how we use AI to improve engineering velocity, reliability, and customer outcomes by enabling safe, governed adoption of GenAI, building agentic systems, and embedding AI-assisted capabilities into our platforms and workflows.

What You’ll Do

· You will introduce AI-enabled capabilities to solve engineering and business problems by identifying high-value use cases, enabling AI adoption and AI-led development practices across teams, and delivering measurable outcomes.

· You will build and ship agentic systems that can plan, execute, and collaborate with humans safely with robust controls, and help build core AI capabilities to scale adoption.

Who You Are

· You also have a strong point of view on practical AI adoption. You can translate real engineering pain points into AI-enabled solutions, select the right patterns and ship systems with strong evaluation, observability, and governance.

Key Skills and Competencies

· Experience in designing and shipping LLM-enabled applications and agentic architectures in production environments, with sound judgment on when not to use agents.

· Experience in responsible AI governance, evaluation, and data safety, including prompt‑injection mitigation, data access controls, secrets handling, policy enforcement, audit logging, offline/online evaluation, observability, red‑teaming, cost/latency monitoring, and safe handling of enterprise and PII data.

The Role:

At Leapwork, we are building the next generation of AI-powered product platforms that help organizations continuously validate and automate their systems.

We believe that modern software is built not only through strong engineering but also through active developer communities and open collaboration. Our engineers are encouraged to experiment, build in the open, contribute to the broader ecosystem, and help shape how automation and AI-driven systems evolve.

As a Sr. Software Engineer, you will work in a fast-paced, team-oriented environment using Agile methodologies. You enjoy solving real customer problems and are comfortable working across the product stack to build meaningful product capabilities.

You understand the “why” behind features and approach development as a way to solve business and user problems rather than simply implementing specifications.

You take ownership of work end-to-end — from understanding the problem, designing the solution, building and validating it, to improving it based on real usage. You are comfortable navigating ambiguity and turning ideas into working product capabilities.

You are excited about the shift toward AI-assisted and AI-driven software development, and you actively leverage AI tools and agents in your development workflow to accelerate experimentation and delivery while maintaining high engineering standards.

Beyond writing code, you believe that strong products are built with strong developer communities around them. You enjoy sharing knowledge, contributing to technical discussions, and helping others learn from what you build.

You actively participate in developer ecosystems, whether through GitHub contributions, open-source collaboration, writing technical blogs, sharing demos, or participating in technical communities. You are comfortable acting as a technical ambassador for the product, helping build awareness and trust within the developer community.

You may have strong technical opinions, but you are never religious about tools or frameworks. You value collaboration, learning from others, and contributing to a culture of continuous improvement.

Most importantly, you enjoy building products that people actually use, and you are motivated by solving meaningful problems rather than simply completing tasks.

Role Responsibilities:

• Build backend services and APIs using Node.js and TypeScript
• Work closely with product teams to rapidly prototype and develop new product capabilities
• Build or integrate AI-driven product features, including systems powered by AI agents
• Leverage AI tools and modern development workflows to accelerate product development
• Help improve the product by incorporating feedback from users and internal teams
• Contribute to the ongoing optimization of internal methods, processes, and systems
• Active participation in technical demos, developer discussions, and community engagement activities to help communicate product capabilities
• Support knowledge sharing through technical walkthroughs, blog posts, or community interactions

Role Requirements:

• 6+ years of development experience building production software products
• Strong experience with Node.js and TypeScript
• Experience building backend services and APIs
• Hands-on experience building or experimenting with AI-powered product capabilities
• Experience designing or integrating AI agents or agentic workflows within product features
• Experience working with LLM APIs or AI services
• Active participation in developer communities, technical forums, or knowledge-sharing platforms
• Experience contributing to open-source projects or maintaining GitHub repositories (personal or professional)
• Comfortable sharing technical knowledge through GitHub projects, blogs, demos, or community discussions
• Strong understanding of JavaScript / TypeScript fundamentals
• Strong understanding of object-oriented and modular programming
• Experience working with asynchronous programming and event-driven systems
• Experience with Git and modern development workflows
• Understanding of cloud-native architectures
• Understanding of Vector databases and scalable data models

Desirable Skills

• Experience building systems where AI agents interact with APIs, workflows, or automation pipelines
• Familiarity with AI-assisted development tools such as Copilot or similar tools
• Experience working with SaaS platforms
• Familiarity with Agile (Scrum) methodology
• Deep Interest in rapid prototyping and experimentation
• Interest in contributing to developer communities, technical content, or product demonstrations
• Strong curiosity about AI-native product development

Job Description

Remarks

＊Please note that you cannot apply for PayPay (Japan-based jobs) or other positions in parallel or in duplicate.

PayPay 5 senses

• Please refer PayPay 5 senses to learn what we value at work.

Working Conditions 

Employment Status

• Full Time

Office Location

• Gurugram (Wework)
  

  ＊The development center requires you to work in the Gurugram office to establish the strong core team.
      

Tesco Media & Insight Platform is a partnership between Tesco, the UK’s largest grocery retailer, and dunnhumby. Fueled by first‑party behavioral data from over 23 million Clubcard holders, we help brands understand consumer behaviors and reach the right customers, at the right time, with the right message across the full marketing funnel. Our closed‑loop measurement connects what customers see with what they buy, helping brands Shape What Britain Buys and maximize the impact of every pound of media investment.

Roles and Responsibilities 

As a Senior AI Engineer, you will be a hands‑on technical contributor designing, building and operating production‑grade GenAI and agentic AI solutions that power Tesco Media & Insight Platform’s global products and services. You will work closely with the AI Engineering Manager, Product, Data Science and Engineering teams to turn business problems into secure, scalable, observable AI systems that deliver measurable value for brands and shoppers.

• Design and implement GenAI and agentic AI solutions on GCP, leveraging Vertex AI (models, endpoints, pipelines, vector search/RAG, Agent Builder) and core GCP services.
• Build AI agents and multi‑step agentic workflows, including tool calling, orchestration, and integrations with internal and external systems.
• Contribute to the design of MCP servers and agent‑to‑agent / agent‑to‑application protocols to enable safe, reliable automation of retail media and insight use cases.
• Work with the AI Engineering Manager and architects to define solution designs, interface contracts and non‑functional requirements (security, reliability, performance, cost).
• Implement security, privacy and governance controls in AI solutions, including safe prompt and tool design, data protection, secrets management and access control.
• Apply DevOps/MLOps practices: contribute to CI/CD pipelines for models, prompts and agents; use infrastructure as code; support environment management and automated testing.
• Implement observability for AI systems: instrument prompts, model calls, tools and agents with tracing, metrics and logs; build and maintain dashboards and alerts.
• Help define and run AI testing and evaluation strategies, including automated tests, offline and online evaluation, red‑teaming, regression suites and human‑in‑the‑loop review flows.
• Collaborate with Retail Media and Insight teams to understand use cases and data, and translate requirements into concrete AI components and services.
• Write high‑quality, well‑tested code in Python (and, where relevant, TypeScript/Java or similar) following team standards for readability, performance and reliability.
• Participate in code reviews, design reviews and incident post‑mortems, and contribute to continuous improvement of our AI engineering practices.
• Stay current on advances in LLMs, agentic frameworks and cloud AI services, and bring forward ideas for how they can be applied to Tesco Media & Insight Platform.

What you’ll need to succeed in the role

• Strong experience in software/data/ML engineering, with hands‑on delivery of AI/ML or LLM‑based solutions into production (not just prototypes).
• Practical experience on GCP and Vertex AI, including deploying models, building pipelines, and implementing RAG/vector search‑based solutions.
• Solid understanding of LLMs and foundation models: transformers at a high level, tokenization, embeddings, context windows, RAG, and the trade‑offs between fine‑tuning, adapters and prompt‑based approaches.
• Hands‑on experience building agentic workflows or AI agents (e.g. tool‑augmented chat, multi‑step workflows, or multi‑agent systems) using one or more modern frameworks or platforms.
• Good grasp of security and safety for AI systems, including prompt and tool design to reduce hallucinations and prompt injection, safe handling of sensitive data, and application‑level guardrails.
• Experience with DevOps/MLOps practices: CI/CD, version control, automated testing, infrastructure as code, monitoring and incident handling in a cloud environment.
• Strong programming skills in Python and experience building and consuming APIs; familiarity with microservices and event‑driven architectures is a plus.
• Ability to design and run evaluation and experimentation for AI features, including quantitative and qualitative measures and, where appropriate, human‑in‑the‑loop review.
• Strong problem‑solving skills, attention to detail, and a willingness to take ownership of complex technical challenges.
• Clear, proactive communication and the ability to collaborate effectively with product managers, data scientists, engineers and commercial stakeholders across locations.

Job Description

 PayPay is looking for a Cloud Infrastructure Engineer for PayPay's Cloud Based payment system. This role will be responsible for the engineering of Cloud Infrastructure Platforms to provide robust, reliable and cost-efficient Platform so that we can deliver the best experience for our growing customers base.

Primary Responsibilities

• Architect and build a robust, scalable and stable infrastructure
• Architect and build Infrastructure that is easily maintainable during patching and upgrades without downtime
• Architect and build Infrastructure with AWS regional level failure tolerance
• Work together with our Security Engineers to provision a secure Infrastructure
• Automations for AWS Deployments to ensure fast delivery of Cloud Services to our developers
• Provide through Automations means for developers to easily deploy resources on AWS

Tech Stack

• AWS:
  • VPC, EC2, ECS, EKS, Lambda, Cloudfront, MWAA, RDS, ElastiCache, DynamoDB, Opensearch, S3, CloudWatch, Cognito, SQS, KMS, Secret Manager, KMS, MSK, SES, Transfer Family, ClientVPN, Shield, WAF, GuardDuty, IAM Identity Center, Organization, WorkSpaces, CodeCommit, CodeBuild, CodeDeploy, CodePipeline, CloudFormation and other services
• Terraform, Github Actions, Prometheus, Grafana, Atlantis, ArgoCD, OpenTelemetry, Wiz, Backstage

Qualifications

• Looking 9+ years of technical and architectural experience in AWS-based infrastructure platforms
• Extensive technical hands-on experience with computing, networking, storage, and analytical services on Latest AWS Services
• Experience with Terraform based infrastructure as code (IAC) on AWS
• Experience in production level infrastructure change management and releases for high traffic & business-critical systems
• Experience in Cloud infrastructure and platform systems availability, performance and cost management
• Experience as an AWS administrator, including Multi AWS organization management, managing 50+ AWS accounts and 100+ users
• Strong understanding of cloud security best practices in Fintech Industry
• Demonstrated skill in programming and scripting languages, including Python, Shell Scripting, Go, and Rust
• Excellent oral, written, and interpersonal communication skills
• Proficiency in either English or Japanese

Preferred Qualifications

• Certified at the AWS Professional or Specialty level
• Experience in payment industry compliance standards such as PCI DSS 
• Bachelor’s degree and above in a Computer Science related field
• Experience with other cloud service providers (e.g GCP, Azure)
• Experience with Kubernetes (CKA, CKAD or CKS)
• Experience in AI/ML infrastructure design and operations
• ​​Experience using and contributing to Open Source tools
• Published papers / blogs / articles
• Bilingual in English and Japanese is nice to have, but not required
• JLPT Level 3 or above
• Leverage AI/LLM-based tools in daily workflows (e.g., code development, reviews, testing, debugging, documentation), while ensuring human oversight, judgment, and accountability drive the final product.

Remarks

＊Please note that you cannot apply for PayPay (Japan-based jobs) or other positions in parallel or in duplicate.

PayPay 5 senses

• Please refer PayPay 5 senses to learn what we value at work.

Working Conditions 

Employment Status

• Full Time

Office Location

• Gurugram (Wework)

　　※The development center requires you to work in the Gurugram office to establish the strong core team.
　　　

Job Description

PayPay India is looking for an Engineering Manager (Java Background) to work on our payment product to deliver the best payment experience for our customers.

Job Description

• Lead the team in its daily tasks, prioritize them, and make decisions based on changing business priorities.
• Structure and facilitate the team’s workflow and development process.
• Coordinate with internal stakeholders across the company to understand their requirements and translate them into the team's technical requirements.
• Fosters the team’s evolution and it’s member’s growth, including, but not limited to, 1:1s and performance evaluation
• Plan for future resources requirements and collaborate with the hiring efforts

Qualifications

• 10+ years of hands-on experience for backend development
• 2+ years of experience for team management
• Track record of designing, developing and supporting highly scalable, responsive web / mobile applications.
• Professional experience in a technical management or leadership role.
• Have a technical mindset and understand complex systems design.
• Have an extreme bias towards action. Basically, have the “Get Things Done” type of attitude.
• Be solutions oriented.
• Be able to maintain high-performance within a high-energy and fast-paced work environment.
• Have excellent oral, written, verbal and interpersonal communication skills. Bilingual in English and Japanese is nice to have, but not required. Proficiency in either language is fine.

Portrait

• Unparalleled speed: Discover for yourself the important things that need to be done and implement ways to reach the best results at the fastest speed possible for the organization.
• Commitment: As a professional, commit to the growth and business goals of the organization and create impactful results by your ownership.
• Logical thinking: Think logically and structurally to bring real communication.
• Curiosity and questioning mind: Keep your curiosity about new things and your challenges along with a continuous questioning mind and enjoy such circumstances in a future-oriented manner.
• Problem solving: Take a proper approach towards both explicit and potential business/organization challenges to lead solutions involving others.
• True opinion and communication skill: Communicate your opinions to others in a flat manner to ensure mutual understanding and to keep things moving forward.
• Leverage AI/LLM-based tools in daily workflows (e.g., code development, reviews, testing, debugging, documentation), while ensuring human oversight, judgment, and accountability drive the final product.

Remarks

＊Please note that you cannot apply for PayPay (Japan-based jobs) or other positions in parallel or in duplicate.

PayPay 5 senses

• Please refer PayPay 5 senses to learn what we value at work.

Working Conditions 

Employment Status

• Full Time

Office Location

• Gurugram (Wework)
  

  ＊The development center requires you to work in the Gurugram office to establish the strong core team.

Job Description

PayPay India is looking for a QA Automation Engineer to enhance our payment systems and deliver the best customer experience. 

Main Responsibilities

• Utilizing the Testing Methodology, analyzes testing requirements as the basis for developing testing scenarios for a test level to be executed on a project.
• Design, create and review test cases based on specifications. Maintain and update test cases.
• Prepare test data, tools, and environment needed for test execution.
• Execute tasks related to the production of the test cases, test scripts, and test data.
• Execute Functional and Non-Functional tests.
• Report found defects, track status of reported defects, and verify fixes.
• Support knowledge management and collaboration through participation in testing discussions, communities and improving testing collateral through lessons learned.
• Provide trainings and instructions to newcomers.
• Serve as SME (Subject Matter Expert) in responsible areas. Develop and provide domain knowledge to support other QA engineers and developers 

Required Skills and Experiences

• At least 4 -8 years of QA Engineer or QA Leader experience.
• Ability to understand and analyze technical specifications. Experience in designing and creating test cases.
• Strong knowledge of QA methodology and QA tools, such as ALM, TestRail, TestLink, QASymphony, etc
• Hands-on Experience in Agile Scrum and Waterfall Software Development Lifecycle.
• Minimum 2 or more years of experience in running and maintaining automated test cases for mobile apps, web apps, or APIs.
• Professional experience in using one of following frameworks/tools - Appium for mobile apps , Selenium for web-based apps, or unirest/Rest Assured for API’s.
• Well versed in using Continuous Integration and Continuous Development tools, like Jenkins/Bitrise or any other.
• Experience in writing SQL, Java, or C# to develop automation frameworks to perform UI, API and backend database testing.
• Experience in creating complex SQL queries to verify results of testing.
• Strong organizational and problem solving skills with attention to detail, Self-driven and proactive, team worker, open-minded, and good communication style.

Preferred Qualifications

• ISTQB or equivalent certificate
• Experience in testing mobile applications (Android and iOS).
• Experience in working with microservices
• Experience in Docker and Kubernetes.
• Experience in working under a fast-paced development environment in IT/Web industry (experience of Agile development is a plus).
• Experience in developing the standardization of QA process and methodology, and/or proposing improvement in QA processes
• Experience in proposing and introducing new QA tools in the test process.
• Experience in the development or QA of systems in the financial and/or payment sector.
• Experience in running performance tests using Gatling/Wrk/Jmeter.
• Experience in bash or other CLI scripting
• Curiosity and passion about learning new technologies is a definite plus
• Leverage AI/LLM-based tools in daily workflows (e.g., code development, reviews, testing, debugging, documentation), while ensuring human oversight, judgment, and accountability drive the final product.

Remarks

＊Please note that you cannot apply for PayPay (Japan-based jobs) or other positions in parallel or in duplicate.

PayPay 5 senses

• Please refer PayPay 5 senses to learn what we value at work.

Working Conditions 

Employment Status

• Full Time

Office Location

• Gurugram (Wework)

　　※The development center requires you to work in the Gurugram office to establish the strong core team.
　　　

Job Description

PayPay India  is looking for a Senior Backend engineer to work on our payment system to deliver the best payment experience for our customers.

Main Responsibilities

• Design large scale systems with high complexity to support our high throughput applications.
• Understand how to leverage infrastructure for solving such large scale problems.
• Develop tools and contribute to open source wherever possible.
• Adopt problem solving as a way of life – always go to root cause! Support the code you write in production.
• [Extra requirements depending on the potential team it has been identified]

Tech Stack

We select the best combination of tech at times.
| Java, Kotlin, Scala
| Spring Boot, JUnit, Reselience4j, Feign
| MySQL/AuoraDB, DynamoDB, ELK, Kafka, Redis, TiDB
| Docker, Kubernetes, ArgoCD, AWS, GCP
| GitHub, IntelliJ, Gradle, Maven, npm/yarn, Flyway, Jenkins, snyk,
| Bigquery, Kibana, Spark
| PlantUML, draw.io, miro.com
| Slack, Zoom

Qualifications

• 6+ years of experience having excellent skills in Java & any other generalized programming language, such as Scala, Python, or Go.
• Interest and ability to learn other coding languages as needed.
• Experience with SQL and NoSQL databases, along with distributed cache.
• Strong fundamentals in data structures, algorithms and object oriented programming.
• In-depth understanding of concurrency and distributed computing.
• Experience implementing platform components such as RESTful APIs, Pub/Sub Systems, and Database Clients.
• Experience with microservices.
• Experience designing high traffic systems.
• Degree in Computer Engineering or Computer Science or 5+ years equivalent experience in SaaS platform development.
• Business of English or Japanese　
• [Extra requirements depending on the potential team it has been identified]

Preferred Qualifications

• • Experience in working for system development in finance, payment, or similar industries.
  • Language ability in Japanese and English is a plus (We have a professional translator but it is nice to have language skills).
  • Experience with AWS services.
  • Leverage AI/LLM-based tools in daily workflows (e.g., code development, reviews, testing, debugging, documentation), while ensuring human oversight, judgment, and accountability drive the final product.
  • [Extra requirements depending on the potential team it has been identified]

Remarks

＊Please note that you cannot apply for PayPay (Japan-based jobs) or other positions in parallel or in duplicate.

PayPay 5 senses

• Please refer PayPay 5 senses to learn what we value at work.

Working Conditions 

Employment Status

• Full Time

Office Location

• Gurugram (Wework)

     ※The development center requires you to work in the Gurugram office to establish the strong core team.
     　

Job Description

PayPay India is looking for a Backend engineer to work on our payment system to deliver the best payment experience for our customers.

Main Responsibilities

• Design large scale systems with high complexity to support our high throughput applications.
• Understand how to leverage infrastructure for solving such large scale problems.
• Develop tools and contribute to open source wherever possible.
• Adopt problem solving as a way of life – always go to root cause! Support the code you write in production.

Tech Stack

We select the best combination of tech at times.
| Java, Kotlin, Scala
| Spring Boot, JUnit, Reselience4j, Feign
| MySQL/AuoraDB, DynamoDB, ELK, Kafka, Redis, TiDB
| Docker, Kubernetes, ArgoCD, AWS, GCP
| GitHub, IntelliJ, Gradle, Maven, npm/yarn, Flyway, Jenkins, snyk,
| Bigquery, Kibana, Spark
| PlantUML, draw.io, miro.com
| Slack, Zoom

Qualifications

• 4+ years of Experience in using Java under professional environment, or if you are non-Java user, excellent skills in generalized programming languages, such as Scala, Python and Go.
• Interest and ability to learn other coding languages as needed.
• Experience with NoSQL databases and distributed cache.
• Strong fundamentals in data structures, algorithms and object oriented programming.
• In-depth understanding of concurrency and distributed computing.
• Degree in Computer Engineering or Computer Science or 5+ years equivalent experience in SaaS platform development.
• Business of English or Japanese　

Preferred Qualifications

• Experience with implementing platform components such as RESTful APIs, Pub/Sub Systems, Database Clients.
• Experience with AWS services.
• Experience in working for system development in finance, payment, or similar industries
• Experience in system design, development of web system which handles massive amount of transactions or requires scalability
• Experience in microservices
• Leverage AI/LLM-based tools in daily workflows (e.g., code development, reviews, testing, debugging, documentation), while ensuring human oversight, judgment, and accountability drive the final product.

Remarks

＊Please note that you cannot apply for PayPay (Japan-based jobs) or other positions in parallel or in duplicate.

PayPay 5 senses

• Please refer PayPay 5 senses to learn what we value at work.

Working Conditions 

Employment Status

• Full Time

Office Location

• Gurugram (Wework)
  

  ＊The development center requires you to work in the Gurugram office to establish the strong core team.
     

About us

At Nanonets, we are building AI-powered automation agents to eliminate manual healthcare admin tasks - helping customers streamline operations and deliver better patient care. We are looking for a Senior Software Engineer who thrives in fast paced startup environments, enjoys shipping impactful products quickly, and can work across the stack to bring our AI agents to life.You’ll work with a small, high-performing team building production-grade AI agents - combining distributed systems, AI integration, and intuitive web platforms.

What You’ll do : 

• Design, develop, and deploy AI agent services that automate healthcare workflows.
• Build scalable APIs, backend services, and sleek frontend interfaces.
• Ship high-quality, maintainable code - fast.
• Collaborate closely with product and AI teams to iterate on agent workflows.
• Monitor, debug, and improve production systems continuously.

What we expect from you :

• 5+ years of hands-on experience in full stack engineering.
• Experience working in a fast-moving startup, with a track record of shipping products quickly.
• Proficiency in at least one backend language (Go or Python) and one frontend framework (preferably React + TypeScript).
• Experience with using LLM APIs and LLM-based applications.
• Strong understanding of web architecture, distributed systems, APIs, and relational databases.
• Ability to write clean, testable code and solve production issues effectively.
• A builder’s mindset: ownership, initiative, and bias for action.

Nice to have :

• Familiarity with US healthcare or other regulated domains.
• Knowledge of DevOps practices, cloud infrastructure, and CI/CD pipelines.

Our Tech Stack :

• Backend: Go, Python
• Frontend: React, TypeScript
• Databases & Infra: PostgreSQL, Redis, AWS/GCP

Why join us ?

• Work on cutting-edge AI agents transforming the healthcare industry.
• Be part of a small, high-impact, no-bureaucracy team.
• Ship products that make a real-world difference for customers.
• Learn fast, grow fast - with competitive compensation & career growth opportunities.

Thinking of applying? Try our resume builder— it's free, fast, and tailored to help you stand out.