Platform Engineering Lead in India

Opportunity Overview: We are looking for a Senior Clinical Configuration Analyst to play a key role in the technical configuration of platform requirements for Cohere’s Platform-as-a-Service (PaaS) clients. Reporting into our Senior Manager, PaaS Value Delivery, you will be part of a small, fast-paced team working directly with client-facing team members to understand and deliver key clinical configurations that are integral to helping new and existing clients meet their prior authorization automation goals. Ultimately, the work you do will have a direct impact on the growth of the company and our ability to assist more patients at a time in their healthcare journey when they need help most. What you’ll do: Ensure thorough understanding of client’s technical requirements to facilitate seamless configuration of platform requirements during new client implementations Test configurability of new product functionality, or enhanced existing functionality, built to accommodate custom client requirements Define test scenarios and success criteria for all new and existing client platform configurations Execute on configuration of platform requirements in accordance with project timelines and client expectations Triage and resolve technical issues, during end-to-end testing or post-implementation, in a timely manner to ensure client satisfaction Serve as a technical SME for client-facing analysts during each stage of the customer lifecycle: providing education and answers to questions around configurability of client platform requirements; occasionally interfacing directly with clients to address issues Collaborate with Product, Development, Design, and Engineering to scope, develop, and implement internal configuration management tools that will help scale configuration work Required Qualifications: Must-haves 3-6 years of professional experience in a Configuration Management role; Bachelor’s degree in Computer Science, Systems Engineering, or related field Problem-Solving

Opportunity Overview: We’re looking for a senior-level automation engineer who will help raise the bar on release quality, environment reliability, and change safety across Cohere’s platform. You’ll partner closely with Product, Engineering, Platform, and SRE to build scalable automation, guardrails, and validation systems that reduce production risk while increasing delivery velocity. This is not a “test scripts only” role. You’ll shape automation strategy, embed quality into the SDLC, and help define how changes move safely from dev → staging → UAT → prod in a fast-moving healthcare platform. You’ll help define how quality scales as Cohere grows. This role has real influence over release safety, platform reliability, and how engineering teams ship software in a regulated, high-impact domain. You won’t just test features — you’ll shape how Cohere delivers them safely to production. What you’ll do: Own and evolve Cohere’s end-to-end test automation strategy across UI, API, config changes, and critical workflows Design and maintain scalable E2E automation frameworks for multi-tenant, payer-specific workflows Build automated validation for deployment guardrails, release readiness, and production change safety Partner with Platform/DevOps to integrate automation into CI/CD pipelines and deployment workflows Create automated coverage for high-risk paths (authorization flows, partner integrations, file pipelines, feature flags, config changes) Drive test reliability, flake reduction, and actionable failure signals Define and enforce quality gates for prod releases, blue/green and canary deployments, and config changes Collaborate with Product and Engineering to ensure business outcomes are testable, measurable, and observable Improve test data management and environment stability to enable reliable automation at scale Mentor engineers on testability, automation best practices, and quality-first development Partner with SRE and Security to ensure production readines

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. About the Role Okta is the identity standard. The Okta Identity Cloud is an independent and neutral platform that securely connects the right people to the right technologies at the right time. We help organizations secure and manage their extended enterprise while transforming their customers’ experiences. With thousands of global customers, 7,000+ app integrations, and over 200 million registered users, we are only getting started. As a member of the Developer Productivity Engineering team, you will tackle high-impact challenges across development environments, AI enablement for engineering, scalability, and stability. Grounded in Okta’s core value— Always Secure. Always On. —your work directly powers developer velocity, system reliability, and software quality at scale. You will act as a force multiplier for our engineering teams by identifying workflow bottlenecks, pioneering AI integrations, establishing best practices for code organization, and maintaining performant development environments. What You’ll Do Design & Automation: Build and ship automated solutions that allow developers to deliver features rapidly without compromising quality, stability, or security standards. Environment Performance & Tuning: Analyze local development workflows, build tools to track operational metrics, and profile/tune development environments (including codebase modifications). AI & Tooling Enablement: Leverage AI technologies across the development stack

We are looking for a highly motivated AI/ML Software Engineer to join the Enterprise Agentic AI Platform team within IT. You will work closely with Business Analysts, and Engineering teams to design, develop, and deploy enterprise AI solutions that improve productivity and automate business workflows across Engineering, Operations, and Manufacturing. What you'll be doing: Design, develop, and deploy Agentic AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI orchestration frameworks. Build scalable AI services and reusable components integrated with enterprise applications such as PLM, SAP, and other business systems. Collaborate with business and IT teams to translate business requirements into AI-driven solutions. Develop secure, scalable APIs and enterprise integrations to enable intelligent workflows and automation. Improve AI solution quality, performance, and reliability through prompt engineering, evaluation, and continuous optimization. Partner with cross-functional teams throughout the Software Development Lifecycle (SDLC), from solution design through deployment and production support. What we need to see: Bachelor's or Master's degree in Computer Science, Information Technology, AI/ML, or a related field. 6+ years of software engineering experience with strong proficiency in Python and backend application development. Hands-on experience with Generative AI, LLMs, RAG, AI agents, REST APIs, and cloud-native application development. Experience integrating enterprise applications and building scalable, production-ready software solutions. Strong analytical, problem-solving, communicatio

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Our mission is to enable effective financial decisions through reliable data, increased efficiency, and automation. We support Marketing, Sales, Seller, Accounting, Tax, Finance and Strategy (F&S), Finance Operations (FinOps), and Treasury functions across automation, data insights, and process improvements. You may work on a wide variety of critical business areas including Seller Systems — Responsible for building the systems and tooling that make sellers and internal revenue teams at Stripe dramatically more productive and effective. We partner with Sales, Finance, Legal, and Product to deliver a single "plane of glass" selling experience that spans deal creation and modeling, negotiation and approvals, contracting, onboarding, and activation. The Seller Systems team composes first‑party, custom Stripe components with best‑in‑class third‑party business systems to deliver configurable, auditable, and globally scalable workflows. Engineers on Seller Systems build services, APIs, integrations, data pipelines, and internal UIs that power seller productivity, reduce time‑to‑activation, improve deal velocity, and enable AI‑driven assistive workflows. Use cases include deal modeling and pricing engines, approval and orchestration platforms, CLM/CPQ integrations, onboarding automation, seller analytics, and AI‑assisted seller tooling. Finance Engineering — Responsible for building the robust and scalable infrastructure that powers

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team The Finance Operations (FinOps) team provides and enhances core business services that are the backbone of Stripe. FinOps uses data and operational excellence to deliver technology solutions, payroll services, operational excellence, and monetization services to Stripe. What you'll do We're looking for a Monetization Operations Analyst to join our growing team. You'll help us improve user experience through accurate and timely onboarding of contracts and workflows, and deliver improvements in our integrated financial systems with business partners, financial colleagues, and engineers. Responsibilities Onboard sold custom contracts into our billing systems. Work with legal contracts with strong attention to detail and accuracy. Develop and manage scalable billing and collection processes for complex user agreements and new business operations. Build scalable and auditable onboarding processes for new and existing users. Partner with internal systems, global deal management, legal, sales ops, internal audit, go-to-market, engineering, and accounting teams to develop and improve processes for contract reviews and to anticipate changing business requirements. Partner with account managers to resolve user inquiries related to onboarding implementation, billing, and collections. Advocate for the customer to internal stakeholders. Share system feedback and insights with Sales, Product Management, Engineering, Support, and Legal on innovation and im

You will be a part of: Storefront (SF) If you are enthusiastic to work on Myntra Storefront customer facing technology platform built for extremely high scale, working on cutting-edge open source technologies, designing & architecting highly performant fault tolerant systems serving 10s of Millions of requests each day scaling to 100s of millions of requests on high sale events then Myntra Storefront is the right place to be. To manage 10s of Millions of requests each day scaling to 100s of millions of requests on high sale events Myntra SF Engineering team builds the technology platform that personalizes our customer’s shopping experience and enables the smooth flow of products from suppliers to our customers’ doorstep. We work on areas such as building massive-scale mobile and web-applications, engaging user-interfaces, user personalization, recommendation & social commerce platforms, content systems, payment systems, search systems, imaging and visualization systems for products etc. We are a technology team where each individual has a huge impact and get to experience the delight of your hard labor & tech excellence being visible to real users. You will work closely with the business in shaping our product and serve hundreds of millions of Indians! You will have the opportunity to be part of a rapidly growing SF organization and gain exposure to all the parts of a comprehensive ecommerce platform. The SF team at Myntra operates within distinct verticals which are (Storefront – Services Platform, Storefront Platforms for personalization & Store Channels (Client Apps-Android/iOS/MWeb/Desktop). Roles and Responsibilities Write maintainable/scalable/e?cient code. Work in a cross-functional team, collaborating with peers during the entire SDLC. Follow coding standards, unit-testing, code reviews etc. Follow release cycles and commitment to deadlines. Qualifications & Experience Experience level of 3 to 5 years of experience in v

At Dscout, we’re building the most flexible and powerful UX research platform on the market—trusted by the world’s top brands in finance (JP Morgan Chase, Intuit, Charles Schwab, PayPal), healthcare (Aya, Headspace), consumer goods (Keen, Verizon, Target, Northface), and tech (Google, Amazon, Facebook, Meta, Spotify, AirBnB). Our tools help teams deeply understand the humans behind their products, so they can build better ones. We are expanding our smart and driven team and would love for you to join us. Building AI-native products is a different problem than building deterministic software: the same input won't always produce the same output. Good product engineering here means designing experiences that stay useful, trustworthy, and easy to understand even when the AI underneath doesn't behave the same way twice — and knowing when that's a product design problem, not just a model problem. We're looking for a Software Engineer with 2-7 years of experience who thinks like a product owner, not just an implementer. You're comfortable being handed a vague, half-formed problem and figuring out what's actually worth building. You default to empathy for the researcher or participant on the other end of the screen, and you'd rather ship something real and learn from it than wait for a perfect spec. You're fluent enough with modern LLM-based systems to build good product experiences on top of them, even if tuning the model itself isn't your job. What you'll do Own end-to-end delivery of product features — from an ambiguous problem statement to shipped, working software real researchers and participants use Partner directly with Product and Design to help define what should be built, not just how to build it Use our design system to make sound, independent calls on smaller UX and interaction decisions, and know when a change is big enough to loop Design in Build the product surfaces (web app flows, dashboards, in-product controls) that make AI-driven behavior understand

At Dscout, we’re building the most flexible and powerful UX research platform on the market—trusted by the world’s top brands in finance (JP Morgan Chase, Intuit, Charles Schwab, PayPal), healthcare (Aya, Headspace), consumer goods (Keen, Verizon, Target, Northface), and tech (Google, Amazon, Facebook, Meta, Spotify, AirBnB). Our tools help teams deeply understand the humans behind their products, so they can build better ones. We are expanding our smart and driven team and would love for you to join us. AI native product is fundamentally different engineering problem than building deterministic software: the same input won't always produce the same output, and "working" means the agent behaves well across the full distribution of real world scenarios, not that it passes a fixed test suite. We're looking for an Applied AI Engineer with 2-5 years of experience building and shipping AI systems used by professionals at enterprise. You're comfortable working with modern LLM-based systems and agentic workflows, and you know how to turn powerful models into reliable product features. You have strong product judgment and think deeply about tradeoffs between LLM approaches and traditional ML when designing solutions. You care about evaluation, iteration speed, and making sure AI systems actually drive measurable business impact reliably . What you'll do Own the production improvement loop across agent behavior, customer and operator feedback, evaluation, experimentation, and verified business outcomes Instrument agent workflows so model interactions, tool use, decisions, failures, human edits, and downstream outcomes can be understood in context Define meaningful quality standards, representative evaluation datasets, regression coverage, and production monitoring. Investigate why agents underperform across context, knowledge, instructions, tools, routing, guardrails, or workflow design Design and ship targeted behavior improvements, including changes to prompting, cont

Job Details: Job Description: In this role, you'll build software capabilities to automate the build, test, and deployment of Intel's Process Design Kit (PDK). A PDK is a collection of artifacts representing Intel's semiconductor process, used by product designers to model, implement, and verify Intel's mobile, desktop, and server products before manufacturing. You'll be a member of the Design Technology Platform organization, working closely with teams in the United States, Bangalore, and Penang to build world-class DevOps infrastructure that shapes the future of deploying PDKs to silicon product development teams at Intel. Qualifications: Bachelor's or Master's degree in Computer Science, Computer Engineering, or another closely related field. 7-12 years of experience with a Bachelor's degree or Master's degree in software development and engineering. Excellent Python programming skills. Expert-level knowledge of pytest concepts. Expert-level experience with GitHub-based Jenkins CI/CD deployment, enablement, and debugging. Proven knowledge of Agile software engineering practices, IT environments, and DevOps principles and processes. Excellent debugging and problem-solving skills. Excellent written and verbal communication skills; ability to present complex issues with clarity to drive decisions. Must have hands-on experience with AI tools and demonstrated experience building AI agents/tools. Exposure to VLSI PDK domain is preferred. Strong team player with proven ability to collaborate effectively across cross-functional and geographically distributed teams. Job Type: Experienced Hire Shift: Shift 1

Job Title Product Manager, G&B Digital Products, PHDSI Job Description Job title: Product Manager , G&B Digital Products, PHDSI Your role: The Product Manager will be responsible for driving the product management activities for digital propositions within Grooming & Beauty, with an initial focus on the Lumea program. The role will work closely with Business, R&D, Digital, UX, Data/AI, Marketing, Regions and Platform teams to ensure strong product definition, roadmap alignment, business value realization and successful delivery of digital experiences. The role requires a strong balance of business understanding, digital product thinking, stakeholder management and execution focus. Own and drive Product Management activities for assigned G&B digital propositions, ensuring alignment with business strategy, consumer needs, market priorities and portfolio direction. Define and maintain the product roadmap, including value proposition, feature priorities, release scope, claims, business case inputs and market readiness needs. Translate business and consumer needs into clear product requirements, working closely with Product Owners, UX, architects, engineering teams, data/AI teams and marketing stakeholders. Ensure strong connection between upstream product strategy and downstream execution across app, cloud, data, AI and connected propositions. Drive prioritization of features and capabilities based on consumer value, business impact, technical feasibility, regulatory needs, cost, performance and delivery timelines. Support development and realization of the business case, including value creation, adoption, engagement, proposition performance and contribution to business outcomes. Lead cross-funct

Role: Senior AI Engineer Location: Hyderabad, India (Hybrid) Department: Product Development About the Role GHX is building a cutting-edge LLM-powered document understanding platform focused on classification, structured data extraction, and intelligent orchestration at scale. This is a high-impact AI engineering role where you will own the full lifecycle—from problem framing to production deployment . Initially, you will focus on prompt engineering and evaluation systems , building the quality foundation for AI performance. Over time, the role expands into agent orchestration, system architecture, and migration of rule-based systems to LLM-driven pipelines . A strong foundation in software engineering (5+ years) is essential. This role demands engineering rigor across both traditional system design and AI system behavior . Core Responsibilities 1. Prompt Engineering Design prompts for diverse document classification and extraction tasks Treat prompts as formal specifications (precise, structured, and edge-case-aware) Develop few-shot, chain-of-thought, and structured output templates Manage prompt lifecycle: versioning, testing, and rollback 2. LLM Output Evaluation Create and maintain ground truth datasets Build automated evaluation pipelines (precision, recall, field-level accuracy) Identify and resolve conceptually incorrect outputs despite surface correctness 3. AI Agent Orchestration Design multi-agent workflows for document processing Implement tool-use patterns and integrate MCP servers Optimize orchestration for scale and efficiency 4. Software Engineering Develop production-grade APIs and backend services Apply Clean Architecture / DDD principles Write maintainable, testable Python code Contribute to CI/CD, deployment, and observability systems 5. Stakeholder Collaboration Act as a bridge between business stakeholders and AI systems Translate product requirements into technical architectures Communicate system behavior, limitations, and quality

Software Engineer - III About the Role GHX is building a next-generation Intelligent Process Automation (IPA) platform powered by LLMs and AI-native document understanding. We extract structured data from complex healthcare procurement documents — Purchase Orders, invoices, contracts — at scale across cloud environments. As a member of the IPA engineering team, you will bridge strong software engineering with applied AI. You will design and ship Python services, integrate LLM APIs, build AI agents, create skills and validate the output of LLMs to build document extraction pipelines, and own evaluation infrastructure that ensures production quality. This is not a research role — it is a hands-on engineering role where AI fluency amplifies solid software craft. Core Responsibilities Python Development & Automation Build and maintain Python-based automation services and IPA workflows Develop platform-agnostic solutions supporting future migration across automation tooling Build reusable libraries, frameworks, and components for automation projects Integrate automation solutions with REST APIs and enterprise applications Deploy and monitor automation bots on AWS (Lambda, ECS, SQS, S3) AI & LLM Integration Integrate LLM APIs (like Anthropic Claude, OpenAI, Azure AI) into production pipelines Design classification and extraction prompts for diverse document types (POs, invoices, contracts) Write prompts that function as formal specifications — unambiguous, edge-case-aware Build and iterate few-shot, chain-of-thought, and structured output templates Own prompt library versioning, rollback strategy, and prompt lifecycle management AI & LLM Integration Integrate LLM APIs (like Anthropic Claude, OpenAI, Azure AI) into production pipelines Design classification and extraction prompts f

ABOUT THIS ROLE GHX is standing up a new Human-in-the-Loop (HiTL) operations team in Hyderabad to support its ADM (Automated Document Management) platform — an AI-powered document processing system replacing legacy UiPath automation for GFax North America. The platform processes over 2.2 million Purchase Orders per year and targets a 75–85% fully-automated (touchless) rate. The team handles every document the AI cannot process autonomously. The Operations Supervisor is building this team from zero and is accountable for everything within it: throughput, field accuracy, team development, day-to-day operations management, and real-time coordination with GHX Engineering and Product teams in the United States. This is a high-visibility, inaugural role — the team’s accuracy and throughput directly determine the speed and confidence with which GHX can expand the ADM platform beyond GFax North America. KEY RESPONSIBILITIES People & Performance Management — 70% Directly supervise 15-20 Document Review Specialists; own rostering across rotational shifts, attendance tracking, and queue capacity planning against daily document volume Manage operations SLA – TAT, Quality, along with people metrics Own day-to-day operations management: shift rosters and week-offs, leave planning, planned & unplanned shrinkage, absenteeism control, and real-time reallocation of staffing to protect SLAs & operations performance metrics Set and communicate daily, weekly, and monthly throughput, AHT, and accuracy targets; monitor individual and team performance against SLA and productivity standards Participate in and present at weekly, monthly, and quarterly business reviews (WBR / MBR / QBR) — performance against KPIs, root-cause analysis of misses, and committed corrective actions Own the full performance cycle for direct reports, including goal setting, mid-year and annual appraisals, with documented performance ratings, development plans, and calibration against peer supervisors Con

JOB TITLE Cloud Compute Engineer A CAREER WITH POINT72’S TECHNOLOGY TEAM As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications. As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business. WHAT YOU'LL DO Design, build, and operate Kubernetes clusters on Amazon EKS, including cluster lifecycle management, networking, autoscaling, and workload scheduling. Manage and optimize EC2-based compute infrastructure, including instance selection, placement strategies, capacity planning, and utilization analysis. Operate and improve ECS-based services where applicable, ensuring consistency across our container runtime environments. Develop and maintain Infrastructure as Code (IaC) using Terraform to provision and manage compute resources at scale. Collaborate with development and platform teams to define compute patterns, containerization standards, and deployment best practices. Monitor compute environments for availability, performance, and cost, driving continuous optimization across the fleet. Contribute to architectural decisions around workload placement, multi-tenancy, OS image and container li