Engineering Architect Jobs

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

About the Team The Customer Experience team serves as a foundational operations pillar at DoorDash, dedicated to resolving friction within the last mile. We architect and oversee an expansive global network of support centers — spanning both teammate-assisted and AI-driven support — obsessing over the user journey to ensure every interaction is seamless and reliable. As the analytics team, our mission is to make every support interaction measurably better: we define what a great resolution looks like, quantify where we fall short, and turn that into a roadmap for product, operations, and AI/ML partners. We are looking for a Manager to lead and grow the analytics team behind our core support experience. About the Role As a Manager on the Customer Experience Analytics team, you'll set the analytical vision for how DoorDash measures and improves customer resolutions across our global network of support teammates and their interactions with our customers. You'll lead and grow a team of data scientists working at the intersection of customer experience quality and operational cost — uncovering opportunities to drive perfect interactions and informing improvements to teammate tooling that leverages AI-driven resolutions. You'll establish a clear measurement framework for resolution quality, own insights to drive strategy and roadmap, and align partners across CX, Product, Engineering, Operations, and AI/ML. This is a high-visibility leadership role: success means better outcomes for customers, a more effective support organization, and a team of data scientists who are growing in their craft. You're excited about this opportunity because you will… Lead, grow, and develop a team of data scientists — providing mentorship, feedback, and clear career development pathways. Set the analytical vision for the core support experience, defining what a great customer resolution looks like and building the metrics to measure it. Uncover opportunities to drive perfect interactions, tr

Job Overview: We are looking for a Senior GenAI Developer to design, build, and productionize agentic AI systems—LLM-powered agents that can plan, use tools, orchestrate workflows, and operate reliably under enterprise constraints. You will own key parts of the agent architecture (planning, tool use, memory, evaluation, safety/guardrails, and observability) and deliver end-to-end solutions across RAG, function/tool calling, multi-agent coordination, and scalable deployment. Key Responsibilities Design and implement agentic systems: single-agent and multi-agent architectures (planner/executor, supervisor-worker, routing, reflection, critique, task decomposition). Build robust tool-using agents: function calling, tool schemas, tool authorization, retries, rate limiting, and sandboxing. Implement RAG + memory patterns: retrieval strategies, hybrid search, context assembly, long-term memory, and grounding/citation behaviors. Develop workflow orchestration for agent execution (state machines/graphs), concurrency controls, and deterministic execution where possible. Productionize GenAI services: APIs, background jobs, streaming responses, caching, and cost/latency optimization. Establish agent evaluation: golden sets, simulation-based evals, LLM-as-judge with mitigations, task success metrics, regression testing. Build observability and safety: tracing, token/tool telemetry, anomaly detection, prompt injection defenses, data leakage prevention, policy enforcement. Collaborate with product, security, and platform teams to deliver enterprise-ready solutions and integrate with internal systems (data, identity, workflow). Mentor engineers, set coding standards, and contribute to architecture reviews and technical roadmaps. Required Qualifications 6+ years software engineering experience; 2+ years building LLM/GenAI systems in production. Strong programming skills in Python (required) and/or TypeScript/Node.js. H

AI Tech Lead – Manager Experience- 8-12 years Job Overview: We are seeking a highly experienced AI Tech Lead to design, develop, and deliver scalable AI-driven applications while leading cross-functional teams. The role involves end-to-end ownership of AI solutions, including architecture design, deployment, and optimization, ensuring alignment with business objectives. The candidate will collaborate with stakeholders, data engineering teams, and product management to build enterprise-grade AI systems leveraging modern cloud and AI technologies. Key Responsibilities / (Person Specifications): Lead implementation and delivery of AI applications across teams. Design end-to-end AI architectures integrating open-source and enterprise tools. Translate business requirements into scalable AI solutions. Define architecture roadmaps and best practices. Build data pipelines, CI/CD, and monitoring systems. Deploy scalable systems using Docker and Kubernetes. Ensure performance, scalability, and security. Mentor teams and drive knowledge sharing. Key Skills / Job Specifications (Mandatory): AI frameworks: LangGraph, AutoGen, CrewAI. Strong Python with TensorFlow, PyTorch, Keras. Knowledge of NLP & Deep Learning (RNN, CNN, LSTM, Transformers). Cloud platforms: AWS / Azure / GCP. Docker, Kubernetes, CI/CD tools. Terraform / CloudFormation (IaC). SQL & NoSQL databases. Distributed systems, REST APIs, GraphQL, microservices.

Data and AI skills are critical for thriving today, and DataCamp is the platform that empowers everyone to learn them. We help individuals and Fortune 1000 companies close the data and AI skills gap through world-class learning, hands-on training, and a global community of expert instructors. In this role, you'll combine deep cloud expertise, technical breadth, and a passion for great didactic experiences to build the next generation of cloud education at DataCamp . About the role This is an individual contributor role. You will collaborate with subject matter experts and leverage in-house-built cutting-edge AI tooling to scale high-quality course creation across cloud platforms (AWS, Azure, GCP) and cloud-adjacent topics such as DevOps, infrastructure-as-code, MLOps, and cloud data engineering. Here's what your day-to-day will look like: Manage the entire content development lifecycle and deadlines. Source and recruit top-tier subject-matter experts as instructors. Collaborate with instructors to create engaging content. Consistently leverage AI tools like Claude Code, Cursor, and more to drive high-quality content production at scale. Design, review, and create content on Cloud platforms, cloud architecture, DevOps, cloud data engineering, and related topics. You will review content from a learner perspective, ensuring it is technically accurate and pedagogically effective. Continuously assess course performance using learner feedback and engagement data to drive improvements. Identify and prioritize existing curriculum gaps or new topics in DataCamp's cloud curriculum. We’re excited about you because you have the following A solid hands-on background working with one or more major cloud platforms (AWS, Azure, or GCP). Relevant cloud certifications (e.g. AWS Solutions Architect, Google Professional Cloud Architect, Azure Administrator) are a strong plus. Broad cloud fluency spanning infrastructure, storage, compute, networking, and managed services, with additiona

Data and AI skills are critical for thriving today, and DataCamp is the platform that empowers everyone to learn them. We help individuals and Fortune 1000 companies close the data and AI skills gap through world-class learning, hands-on training, and a global community of expert instructors. In this role, you'll combine deep cloud expertise, technical breadth, and a passion for great didactic experiences to build the next generation of cloud education at DataCamp . About the role This is an individual contributor role. You will collaborate with subject matter experts and leverage in-house-built cutting-edge AI tooling to scale high-quality course creation across cloud platforms (AWS, Azure, GCP) and cloud-adjacent topics such as DevOps, infrastructure-as-code, MLOps, and cloud data engineering. Here's what your day-to-day will look like: Manage the entire content development lifecycle and deadlines. Source and recruit top-tier subject-matter experts as instructors. Collaborate with instructors to create engaging content. Consistently leverage AI tools like Claude Code, Cursor, and more to drive high-quality content production at scale. Design, review, and create content on Cloud platforms, cloud architecture, DevOps, cloud data engineering, and related topics. You will review content from a learner perspective, ensuring it is technically accurate and pedagogically effective. Continuously assess course performance using learner feedback and engagement data to drive improvements. Identify and prioritize existing curriculum gaps or new topics in DataCamp's cloud curriculum. We’re excited about you because you have the following A solid hands-on background working with one or more major cloud platforms (AWS, Azure, or GCP). Relevant cloud certifications (e.g. AWS Solutions Architect, Google Professional Cloud Architect, Azure Administrator) are a strong plus. Broad cloud fluency spanning infrastructure, storage, compute, networking, and managed services, with additiona

Data and AI skills are critical for thriving today, and DataCamp is the platform that empowers everyone to learn them. We help individuals and Fortune 1000 companies close the data and AI skills gap through world-class learning, hands-on training, and a global community of expert instructors. In this role, you'll combine deep cloud expertise, technical breadth, and a passion for great didactic experiences to build the next generation of cloud education at DataCamp . About the role This is an individual contributor role. You will collaborate with subject matter experts and leverage in-house-built cutting-edge AI tooling to scale high-quality course creation across cloud platforms (AWS, Azure, GCP) and cloud-adjacent topics such as DevOps, infrastructure-as-code, MLOps, and cloud data engineering. Here's what your day-to-day will look like: Manage the entire content development lifecycle and deadlines. Source and recruit top-tier subject-matter experts as instructors. Collaborate with instructors to create engaging content. Consistently leverage AI tools like Claude Code, Cursor, and more to drive high-quality content production at scale. Design, review, and create content on Cloud platforms, cloud architecture, DevOps, cloud data engineering, and related topics. You will review content from a learner perspective, ensuring it is technically accurate and pedagogically effective. Continuously assess course performance using learner feedback and engagement data to drive improvements. Identify and prioritize existing curriculum gaps or new topics in DataCamp's cloud curriculum. We’re excited about you because you have the following A solid hands-on background working with one or more major cloud platforms (AWS, Azure, or GCP). Relevant cloud certifications (e.g. AWS Solutions Architect, Google Professional Cloud Architect, Azure Administrator) are a strong plus. Broad cloud fluency spanning infrastructure, storage, compute, networking, and managed services, with additiona

Data and AI skills are critical for thriving today, and DataCamp is the platform that empowers everyone to learn them. We help individuals and Fortune 1000 companies close the data and AI skills gap through world-class learning, hands-on training, and a global community of expert instructors. In this role, you'll combine deep cloud expertise, technical breadth, and a passion for great didactic experiences to build the next generation of cloud education at DataCamp . About the role This is an individual contributor role. You will collaborate with subject matter experts and leverage in-house-built cutting-edge AI tooling to scale high-quality course creation across cloud platforms (AWS, Azure, GCP) and cloud-adjacent topics such as DevOps, infrastructure-as-code, MLOps, and cloud data engineering. Here's what your day-to-day will look like: Manage the entire content development lifecycle and deadlines. Source and recruit top-tier subject-matter experts as instructors. Collaborate with instructors to create engaging content. Consistently leverage AI tools like Claude Code, Cursor, and more to drive high-quality content production at scale. Design, review, and create content on Cloud platforms, cloud architecture, DevOps, cloud data engineering, and related topics. You will review content from a learner perspective, ensuring it is technically accurate and pedagogically effective. Continuously assess course performance using learner feedback and engagement data to drive improvements. Identify and prioritize existing curriculum gaps or new topics in DataCamp's cloud curriculum. We’re excited about you because you have the following A solid hands-on background working with one or more major cloud platforms (AWS, Azure, or GCP). Relevant cloud certifications (e.g. AWS Solutions Architect, Google Professional Cloud Architect, Azure Administrator) are a strong plus. Broad cloud fluency spanning infrastructure, storage, compute, networking, and managed services, with additiona

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE As the Manager of GTM Systems (Quote to Revenue), you will lead our core engineering team in Bangalore to architect and scale Everpure’s enterprise billing and revenue engine. You will serve as the critical technical bridge between US business stakeholders and our local engineering squad, embedding cutting-edge AI tools directly into the development lifecycle to drive unprecedented speed and automation. This hands-on leadership role puts you at the center of Everpure’s growth, directly impacting our lead-to-cash velocity and financial compliance across global markets. WHAT YOU'LL DO Lead and Scale AI-Accelerated Engineering: Direct a team of 5–8 cross-functional developers and QA engineers, integrating modern AI tools (such as Claude, Boomi AI, and Salesforce Agentforce) into daily workflows to drastically reduce code generation time, streamline unit testing, and elevate team performance. Architect End-to-End Quote-to-Revenue Solutions: Own the technical execution across Salesforce CPQ, Boomi middleware, and Zuora billing to optimize complex product catalogs, pricing waterfalls, automated quote generation, and subscription accounting. Bridge Global Stakeholder Alignment: Partner closely with US-based Product, Finance, and RevOps leaders to translate complex revenue operations and financial compliance goals into clear, scalable system designs and technical user stories. Ensure Platform Governan

We believe communication belongs to everyone. We exist to democratize phone service. TextNow is evolving the way the world connects and that's because we're made up of people with curious minds who bring an optimistic, yet critical lens into the work we do. We're the largest provider of free phone service in the nation. And we're just getting started. Join us in our mission to break down barriers to communication and free the flow of conversation for people everywhere. TextNow is looking for motivated Site Reliability Engineer to own infrastructure, monitoring, logging, ci/cd, reliability and everything in between! This role is about impact at scale. You’ll shape how TextNow builds and operates its systems in an AI-first environment where intelligent tooling is embedded into everyday engineering practice. Using AI is not optional, it’s expected. From design and architecture to implementation, testing, debugging, documentation, and operational analysis, you will actively leverage AI tools to increase velocity, improve code quality, and make better technical decisions. We provide a robust suite of AI-powered development tools and workflows to support you, and we expect you to continuously evolve how you use them to raise the bar for efficiency, clarity, and product excellence across the organization. What You'll Do Ensure System Reliability: Design, build, and maintain scalable, resilient, and highly available systems to support TextNow’s infrastructure and services. Automation & Infrastructure as Code: Develop and maintain automation using Terraform, Ansible, and other tools to enable efficient deployment, scaling, and operations of cloud-based systems (AWS preferred). Incident Response & On-Call Support: Participate in an on-call rotation, troubleshoot issues, and drive incident resolution to minimize downtime and improve syste

Data Engineer, Data Platform About the Role We are building out our Data Platform team at Sigma, with a relentless focus on developing data models that fuel trusted insights across the company. As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both internal and external (demo) use cases. Reporting to the VP of Data & Revenue Engineering, this is a high visibility role with the opportunity to work on greenfield projects. If you’re a data engineer with a builder mindset who wants to leverage a best-in-class stack, and genuinely is invested in Sigma’s mission, let’s chat! What You Will Be Doing Architect and manage our production data pipelines in Snowflake and how they are consumed in Sigma ( Tech we use : Fivetran, dagster, dlt, terraform, dbt, Snowflake, Sigma, Hightouch, Metaplane) Build foundational processes for scaling our demo asset data across various Cloud Data Warehouses Scale our terraform deployment across all of our Snowflake assets Continue to advance our data governance policies Work cross functionally to accomplish all of the above! You’ll work across Product, Engineering, GTM—with users of all skills and levels Qualifications We Need Strong knowledge and experience of working with APIs and building data pipelines from various systems into Cloud Data Platforms (e.g., Snowflake, Databricks) Strong communication and collaboration skills. You will primarily partner with the Analytics and Infrastructure Engineering teams internally at Sigma; your ability to work and collaborate closely with them will be integral to your success. Experience deploying data governance frameworks with a scalable and repeatable process Ability to thrive in ambiguous environments and get stuff done. We move fast and iterate quickly, and we want you to feel empowered to do exactly that 3+ years of relevant experience wor

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Site Reliability Engineering at Affirm is a small, yet crucial, team that helps our Engineering partners to “Operate What They Own” with excellence to protect their customers’ experience. SRE accomplishes this through defining frameworks and best practices for operating applications, building tooling, and providing training and consulting. Some of the many SRE responsibilities are: Providing data and visibility to teams and leadership on application performance Guiding the development of SLOs Driving the Incident Management and Analysis process Steering the implementation of Change Management and Deployment practices Engaging in service and architectural conversations Recommending observability and alerting configurations The SRE team benefits from experience across many domains including: infrastructure, platform, and distributed systems capacity management, load and chaos testing automation, observability, and configuration management development and product experience The SRE team is seeking motivated software and systems engineers with the experience to build, iterate on, and expand incident lifecycle, reliability, and resilience practices throughout Affirms Engineering organization and beyond. What You'll Do: You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery. You will support your peers and stakeholders in the product development lifecycle by collaborating with infrastructure, product management, developer experience & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. You will proactively identify technical solutions

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Site Reliability Engineering at Affirm is a small, yet crucial, team that helps our Engineering partners to “Operate What They Own” with excellence to protect their customers’ experience. SRE accomplishes this through defining frameworks and best practices for operating applications, building tooling, and providing training and consulting. Some of the many SRE responsibilities are: Providing data and visibility to teams and leadership on application performance Guiding the development of SLOs Driving the Incident Management and Analysis process Steering the implementation of Change Management and Deployment practices Engaging in service and architectural conversations Recommending observability and alerting configurations The SRE team benefits from experience across many domains including: infrastructure, platform, and distributed systems capacity management, load and chaos testing automation, observability, and configuration management development and product experience The SRE team is seeking motivated software and systems engineers with the experience to build, iterate on, and expand incident lifecycle, reliability, and resilience practices throughout Affirms Engineering organization and beyond. What You'll Do: You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery. You will support your peers and stakeholders in the product development lifecycle by collaborating with infrastructure, product management, developer experience & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. You will proactively identify technical solutions

About the role As a Forward Deployed Engineer (FDE) focused on Inference & Post-Training, you will be a hands-on technical partner to our most strategic customers — production AI teams looking to leverage high quality models and do inference at scale. For us, FDE is not a replacement for a Solutions Architect; you will partner with our SAs as a deep-domain specialist in inference optimization, fine-tuning pipelines, and production deployment. As key contributors to both the CX, Engineering, and Sales organizations, FDEs add tremendous value by ensuring we can meet the requirements of our most complex POCs, facilitate successful platform adoption, and guide tailored optimization efforts — directly impacting customer success, company growth, and the hardening of our core platform. Must be a permanent resident or citizen of Singapore. Responsibilities Inference Engine Optimization: Select, configure, and optimize inference engine based on hardware, model architecture, and workload profile Configuration & Performance Tuning: Develop configuration updates to win critical POCs, benchmarks, and optimize customer deployments; tune KV cache, apply speculative decoding, determine optimal tensor parallelism, and determine quantization strategy to hit throughput and latency targets. Post-Training & Fine-Tuning: Drive hands-on RL training runs and optimize system design; guide customers through LoRA, SFT, DPO, RLHF, and GRPO pipelines from experimentation through production. Strategic Customer Alignment: Act as the primary technical point of contact for aligned strategic accounts — monitoring and optimizing endpoint configurations, helping customers get the most out of the platform, and collaborating to ensure we hit critical milestones. Opinionated Onboarding: Establish direct alignment with strategic customers at onboarding; ensure the right inference and post-training configurations are in place from day one to improve time-to-value. Product Feedback Loop: D

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