ResponsibilitiesArchitectural Governance: Define and maintain global architecture standards, design patterns, and best practices for Power Platform solutions across the enterprise. Technical Leadership: Lead and mentor a crew of 6-10 developers, providing hands-on guidance, code/solution reviews, and technical oversight to ensure high-quality product delivery. Advanced Development: Handle complex development requirements and "research spikes" to evaluate new features, tools, or frameworks (e.g., PCF, AI Hub, Custom Connectors). ALM Strategy: Own and optimize the Power Platform Application Lifecycle Management (ALM) process using Power Pipelines, PAC CLI, and code-first DevOps practices. Solution Design: Design efficient, high-performance Cloud Flows and applications utilizing deep expertise in REST API integration, JSON manipulation, and XPath.

ResponsibilitiesProject & Resource Management Manage 10-15 support engineers (L2-L3) Lead and manage automation support projects from ingestion to ongoing, ensuring they are supported as per AOC delivery model and framework. Daily/weekly standups and operations metrics reviews with support, product and implementation teams Weekly and monthly review meetings with stakeholders on current/future support pipeline Process Analysis and Improvement Conduct thorough analysis of existing support processes to identify inefficiencies, instabilities, and areas for improvement. Develop and define best practices in automation support, monitoring, maintenance and contribute to our knowledge base (wikis) and standards. Team Management Foster a culture of continuous learning and improvement within the support team. Maintain Skill register for all resources, identify capabilities and training needs Measure, Ensure and Report team member efficiency and productivity to ensure optimal staffing with redundancy in place. Collaboration and Communication Proactively inform about any errors, outages or unexpected issues that may affect project outputs.

ResponsibilitiesHandle end-to-end recruitment for domestic IT requirements Source and screen candidates through portals like Naukri, LinkedIn, References, etc. Expertise in hiring for contract positions, especially skills like Pega, Camunda, Java, and ServiceNow Coordinate interviews with candidates and hiring managers Maintain candidate pipelines and ensure timely closures Manage candidate onboarding for selected resources. Maintain recruitment reports and documentation Stake holder management, client handlingQualification & ExperienceProven experience in Contract Staffing Strong understanding of various IT skills and job roles Excellent communication and stakeholder coordination skills Ability to work in a fast-paced hiring environment Good knowledge of recruitment tools and ATSExperience: 4 - 8 Years

ResponsibilitiesBuild agentic AI applications that solve real business problems Design and implement RAG systems, multi-LLM pipelines, and tool-use architecturesDevelop, test, and deploy production-grade APIs and backend servicesBenchmark and evaluate LLM outputs for accuracy, cost, and latencyContribute to internal AI frameworks and reusable component librariesParticipate in architecture reviews and client solution design Qualification & ExperienceMust have: Strong Python — data structures, APIs, async programming Must have: Fundamentals of ML, NLP, and Generative AI Good to have: Java (Core + Advanced), FastAPI/Flask, Docker basics Mindset: Strong problem-solving, curiosity to go deep, bias for building over reading Eligibility B.Tech / BE (CSE / IT) — 2025 or 2026 graduates Minimum 70% aggregate

Responsibilities Assist in designing and executing manual and automated test cases. Support automation testing using Selenium and learn BDD practices. Perform manual testing for new features and bug fixes. Execute test cases and help analyze test results. Identify, log, and track defects under guidance from senior team members. Participate in end?to?end testing activities. Document test cases, test results, and defects. Learn and follow best practices in software testing and quality assurance.Qualification & ExperienceBasic understanding of Manual Software Testing concepts Fundamental knowledge of Selenium for automation testing Basic knowledge of Java programming Understanding of API testing using tools like Postman or Insomnia Awareness of REST Assured for API testing (basic exposure is sufficient) Basic knowledge of SQL for database validation Familiarity with Unix/Linux commands Understanding of SDLC & STLC Exposure to Cucumber, BDD, or any automation frameworksExperience with any academic or personal testing projects.

Responsibilities· Regular monitoring of regulatory data sources for new data / listings (Sanctions, PEP, etc.) · Verify, validate and ensure correctness and completeness of data generated through AI / ML solutions · Build data manually from unstructured sources as needed · Extend support to implement solutions that converts unstructured data to structured / usable information · Prepare test cases / scenarios for newer implementations and execute such tests during releases · Monitor structural changes to data and keep track of major events impacting data, product and customers · Track changes/bug fixes and ensure they are till implemented appropriately · Execute periodic reviews and controls as described in the processes · Ensure MI is maintained as per schedules and extend support in automating MI and reporting processes · Publish weekly reports on the activities and status of each of the regulatory lists · Extend Ad-hoc support to the team when needed · Daily reporting of given tasksQualification & Experience· Education: Bachelor’s degree (min.) · Experience: 0 to 1 years · Must have skills: Proficiency in MS Excel, ability to interpret unstructured data and create structured data · Good to have skills: Understanding on watchlist screening processes, NumPy, Pandas and basic understanding of data frames · Candidate should be open to work in rotational shifts and rosters covering weekends

Responsibilities Provide L1/L2 support for applications and infrastructure in a Unix/Linux environment. Monitor systems and services using AWS CloudWatch and other monitoring tools like Grafana etc. Assist in troubleshooting issues related to AWS services such as EC2, S3, EKS, and VPC. Support Kubernetes-based deployments and help with pod, node, and cluster-level troubleshooting. Participate in CI/CD pipeline support using Jenkins and Git. Assist in incident, problem, and change management activities as per ITIL processes. Support ETL jobs and handle basic database-related issues. Document issues, resolutions, and operational procedures clearly. Collaborate with cross-functional teams to ensure timely resolution of incidents. Qualification & ExperienceBasic to intermediate knowledge of Unix/Linux commands and shell scripting. Understanding of AWS Cloud and core services (CloudWatch, EC2, S3, EKS, VPC). Hands-on knowledge of Kubernetes concepts and troubleshooting. Solid understanding of Git, Jenkins, CI/CD pipelines, and DevOps practices. Working knowledge of ETL processes and databases such as: PostgreSQL MongoDB Ab Initio (good to have) Understanding of ITIL processes, especially: Incident Management Problem Management Willingness to work 24/7 rotational shifts, including weekends. Good to Have AWS Certification (Cloud Practitioner / Associate level or higher) Soft Skills Excellent written and verbal communication skills. Strong problem-solving and analytical abilities. Eagerness to learn and adapt in a fast-paced support environment. Team player with a proactive attitude.

ResponsibilitiesYou will leverage your strong ML/DL/Statistics background to build new and next generation of ML based solutions to improve the quality of ads recommendation and leverage various optimization techniques to improve the campaign performance. You will mine and extract relevant information from Swiggy's massive historical data to help ideate and identify solutions to business and CX problems. You will work closely with engineers/PMs/analysts on detailed requirements, technical designs, and implementation of end-to-end inference solutions at Swiggy scale. You will stay abreast with the latest in ML research for Ads Bidding algorithms, Recommendation Systems related areas and help adapt it to Swiggy's problem statements. You will publish and talk about your work in internal and external forums to both technical and layman audiences. Opportunity to work on challenging and impactful projects in the logistics domain Collaborate with cross-functional teams, including software developers and product managers, to integrate data-driven solutions into our systems Develop and deploy machine learning and deep learning models Take ownership of projects from inception to delivery, ensuring high-quality and impactful results.Qualification & ExperienceBachelors or Masters degree in a quantitative field with 0-2 years of industry/research lab experience Required: Excellent problem solving skills, ability to deconstruct and formulate solutions from first-principles Required: Depth and hands-on experience in applying ML/DL, statistical techniques to business problems Preferred: Experience working with ‘big data’ and shipping ML/DL models to production Required: Strong proficiency in Python, SQL, Spark, Tensorflow Required: Strong spoken and written communication skills Big plus: Experience in the space of ecommerce and logistics Experience in Generative AI Proven track record of developing and shipping ML and DL data products Experience in Agentic AI , LLMS and NLP Proficiency in Python

ResponsibilitiesFormulate and implement innovative solutions to business problems using state of the art Machine Learning/Deep Learning models Leverage Swiggy’s rich data at scale to build deeply personalized recommendation systems Drive high-impact initiatives by closely collaborating with Product, Engineering, and Business teams. Build and scale machine learning models across domains like supply chain, logistics, Ads, Search, and customer experience Leverage our mature ML infrastructure to deploy models and conduct experiments Work with and mentor fellow Data Scientists Experiment, innovate, and deploy cutting-edge ML solutions at scale Contribute and co-own the product roadmap.Qualification & Experience5–8 years of experience in Machine Learning, Applied Statistics, and Data Science. Strong understanding of model deployment, experimentation, and impact measurement. Hands-on experience with Python, ML frameworks, big data tools, and real-world systems. Passionate about solving complex problems across Ads, Search, logistics, and personalization.

ResponsibilitiesReal problems at real scale: Systems that affect millions of orders, thousands of dark stores, and real P&L Direct access: No layers between you and the teams you're solving for. You see the problem, you ship the fix. Shape the platform: Your field work defines what the Central AI team builds. Direct input into roadmap and architecture decisions. Founder-like ownership: You're essentially the CTO of AI for your embedded domain Career leverage: FDE is the fastest path to becoming a technical leader who understands both AI and operations at scale Qualification & Experience2+ years shipping production systems with real traffic, real users, real constraints (exceptional freshers who are AI power users with proof of work will also be considered) OR: Technical founder / early engineer at a startup with demonstrable AI impact Trade-off fluency: latency vs accuracy, cost vs reliability, autonomy vs predictability Strong in Python or TypeScript, LLMs, orchestration frameworks, system design