Technical Solutions Specialist Jobs

Senior Technical Program Manager — 2 Locations. Apply via Workday.

Senior Technical Program Manager, Cloud Infrastructure — 2 Locations. Apply via Workday.

Construction Technical Specialist — 2 Locations. Apply via Workday.

Sr Technical Product Owner — 3 Locations. Apply via Workday.

... Facility: GREATLAKES BILASPUR FM Qualification: Diploma Job Code: IJP550821 | Source: Sodexo India

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 The FlashArray team builds an innovative, high-performance, and highly available portfolio of products designed for demanding, mission-critical applications. While we deliver a hardware storage array, over 90% of our engineering team focuses on software engineering. Our customers value FlashArray for its simplicity of management, continuous feature upgrades, and ability to stay on the cutting edge without downtime. Recently, we extended these capabilities into the public cloud with CloudSnap and Cloud Block Store for AWS, enabling customers to leverage cloud agility for both traditional IT and cloud-native applications. WHAT YOU’LL DO Design & Implement: Create innovative algorithms and technologies for high-performance systems targeting six-nines (99.9999%) reliability. End-to-End Ownership: Lead feature innovation from initial concept through to shipped product. Problem Solving: Analyze and resolve complex technical challenges through persistent problem-solving and technical insight. Collaborate & Deliver: Partner closely with smart, collaborative peers to deliver features that directly enhance customer experience and satisfaction. Learn & Grow: Continuously expand domain expertise in systems software within a supportive, knowledge-sharing environment. WHAT YOU BRING Software Development Experience: 3+ years of professional development experience using C, C++, Python, Go, Java, or relat

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 Our engineering team thrives on challenging the norm and drawing from diverse technical backgrounds to build some of the industry’s most reliable, intuitive systems. We are forming a dedicated AI Applications team focused on building systems, tools, and processes that elevate the developer experience and accelerate innovation. We are seeking an experienced Senior Platform Engineer to lead the "Inner Loop" of AI development. In this role, you will bridge high-velocity AI experimentation and enterprise-grade production infrastructure ensuring LLM applications, RAG pipelines, and agentic workflows are built, tested, and deployed with high reliability and efficiency. WHAT YOU’LL DO Deliver Platform Self-Service: Design internal APIs and abstractions allowing engineers to provision AI-ready environments complete with model weights, vector databases, and event streams via single-command automation. Build Agentic & Go-Based Automation: Develop robust, type-safe internal tooling and AI agents in Go and Python to automate root-cause analysis, disaster recovery, and proactive infrastructure optimization. Scale Event-Driven AI Pipelines: Architect asynchronous processing systems using Kafka and RabbitMQ to trigger dynamic infrastructure scaling and handle high-volume data streams like long-running document ingestion. Ensure Reproducible Deployments: Maintain "Golden Path" deployment standards using Docker and Kubernetes

About the Role The Enterprise Agent Evals & Efficiency team makes Perplexity's agents better at completing real work across enterprise connectors, tools, and data. Our goal is to help agents choose the right tools, use the right context, and complete complex workflows reliably, with less time and compute. This team owns the improvement loop: define what successful work looks like, build evaluations that measure it, understand where agents fail, and ship changes that improve outcomes. This is a hands-on engineering role with end-to-end ownership, from building realistic enterprise evaluation environments to shipping improvements across the agent harness, tools, and skills. You'll create complex scenarios spanning connected systems, data, and permissions, use them to identify where agents struggle, and improve the tools agents call, the skills they follow, the context they receive, and the models they use. Working with AI Research, Connectors, and Platform teams, you'll turn experimental results into measurable gains in task success, latency, and cost per successful task. The goal is not just to measure agents, but to make more enterprise work reliable and practical to automate. Key Responsibilities Build realistic enterprise evaluation environments spanning connected applications, representative datasets, user roles, and permissions, with complex, multi-step workflows and reproducible system state. Own evaluation infrastructure, task suites, and automated graders that measure how well agents complete enterprise work, calibrated against human judgment and grounded in end-to-end outcomes. Analyze agent trajectories and production failures, identify root causes, and ship improvements across the agent harness, tools, and skills that measurably improve task success and reliability. Develop reusable skills and improve tool descriptions, schemas, and result handling so agents can select the right tools, execute workflows correctly, and recover from errors with fewer unn

About the Role The Enterprise Trust & Governance team builds the control plane that lets the world’s largest organizations deploy Perplexity broadly and with confidence. Computer and our agents work across a growing share of our customers’ environments, tools, and models. For administrators, that makes precise, enforceable control essential: who can do what, with which data, through which agents, and within what usage limits. This team makes those controls easy to manage, reliable and consistent across every product, and transparent to the people accountable for them. This is a product and platform engineering role with end-to-end ownership, from shaping the architecture and policy models to shipping the experiences our customers’ administrators and security teams use every day. You’ll work across product and infrastructure teams to turn complex enterprise requirements into reusable primitives and intuitive controls. The scope spans identity and provisioning, fine-grained role-based access across connectors, tool actions, and models, customer-managed encryption keys, admin APIs, audit logs, and policy and usage controls. Strong governance helps enterprises move from pilots to company-wide rollouts and gives them the confidence to entrust agents with greater responsibility over time. Key Responsibilities Own enterprise identity and provisioning, including SSO (SAML/OIDC), SCIM, WorkOS integrations, and support for identity providers such as Okta and Microsoft Entra ID. Build the permissions platform, with fine-grained roles and permissions for connectors, tool actions, models, and model effort levels, enforced consistently across products and agent workflows. Design and ship secure, well-documented admin APIs for audit logs, members, groups, roles, and settings. Build policy controls for model and feature availability, staged rollouts, model deprecations, usage and spend limits, alerts, and cost-center allocation. Build admin-facing analytics for adoption, usage,

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 a core member of the FlashBlade product team—one of Pure Storage’s fastest-growing business units—you will help build and evolve our scale-out, all-flash file and object storage platform built for high-performance AI, modern backup, and real-time analytics. You will tackle complex distributed systems challenges at the intersection of algorithms, operating systems, and high-concurrency architectures to deliver six-nines reliability. Collaborating closely with Product Management, Validation, Support, and customers, you will directly shape how modern enterprises process and manage data at massive scale. WHAT YOU'LL DO Architect & Deliver Core Storage Systems: Drive end-to-end design, implementation, and delivery of high-performance distributed systems algorithms, taking innovations from early concept to production-grade shipped features. Solve High-Impact System Complexities: Analyze and resolve complex architectural, kernel, and concurrency bottlenecks across storage platforms, ensuring continuous enterprise-grade uptime and operational resilience. Collaborate Across Engineering Teams: Partner with cross-functional stakeholders—including Product Management, System Validation, and Customer Support—to align technical design proposals with evolving business and customer requirements. Elevate System Quality & Reliability: Own the overall software quality, performance, and maintainability of enterprise-scale d

Job Requisition ID # 26WD100979 Position Overview We are seeking an experienced product and technical marketing professional with a mechanical design and engineering background to support and expand the Fusion design portfolio in EMEA. Autodesk Fusion brings CAD, CAM, CAE, PCB, PDM, and PLM together on one cloud platform at a price that puts professional tools within reach of every engineer and every shop. EMEA is home to some of the world’s most demanding design and manufacturing customers, and they don’t buy generic messaging. They buy from people who understand their workflows, their tools, and their constraints. You will own messaging and positioning for Fusion design in the region, develop technical assets, and produce enablement content that empowers our go-to-market teams to win against entrenched incumbents such as SolidWorks, Inventor, Onshape, NX, and Creo. This role requires someone who has worked as an engineer or designer, understands how products are modeled, simulated, documented, and released to manufacturing, and can translate technical capabilities into compelling business value. Ideal candidates will bring an experimentation mindset and continuously find ways to use AI to scale themselves and the team. Responsibilities Product Marketing Own the Autodesk Fusion design story and point of view for EMEA, including AI-enabled design workflows, adapting the global narrative to regional segments, industries

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You'll own durability and cost at petabyte scale, from streaming and batch replication between origins, to garbage collection over billions of objects. You'

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview As a Member of Technical Staff in Post-Training Data Infrastructure, you will build and own the pipelines that produce the post-training data for our large language models (LLMs), from SFT and RL data to synthetic and human-annotated data. You will work closely with researchers and annotation teams so they can iterate on data as quickly as they iterate on models. Key Responsibilities Build and maintain data pipelines for SFT, preference, and RL post-training data. Own dataset quality, versioning, and reproducibility. Turn research data recipes into production-grade, reusable components. Scale model inference for data generation and model-based grading. Design data formats and schemas that keep post-training datasets consistent and efficient to train on. Collaborate with researchers and engineers to make sure data pipelines keep pace with the needs of cutting-edge language models. Qualifications Strong software engineering skills. Experience designing and building large-scale data pipelines for machine learning, ideally for LLM post-training. Track record of running distributed data processing and model inference at

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Key Overview: As a Member of Technical Staff in Post-Training, you will train our large language models (LLMs) with reinforcement learning and develop methods that help them generalize beyond the distribution they were trained on. You will design the training recipes, environments, and evaluations that tell us whether a model has truly learned a skill or has only fitted its training tasks, and turn what works into the recipes behind our production models. You will work closely with the post-training data infrastructure, evaluation, and pre-training teams. Key Responsibilities Design, run, and analyse large-scale RL post-training experiments (e.g., RLHF, RL from verifiable rewards). Research and develop methods that improve out-of-distribution generalization, such as reward design, environment and task diversity, curricula, and regularization. Build held-out evaluations that measure generalization to unseen tasks, domains, and formats, and that catch reward hacking and benchmark overfitting. Diagnose training dynamics and failure modes, including instability, reward over-optimization, and capability regressions. Turn successful r

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview As a Senior Engineering Lead, you will be a hands-on technical leader within the Platforms & Infrastructure team in Enterprise Operations & Technology, helping a growing cloud platform organization raise its engineering maturity and delivery effectiveness. This high-visibility role applies GenAI, AIOps, automation, and modern AWS engineering practices to reduce platform toil, remove operational delays, and design self-service, self-healing capabilities. By codifying reusable patterns, automation frameworks, and guardrails, this role enables application teams to modernize with less platform friction while maintaining secure, scalable, and resilient outcomes in a regulated environment. Our Impact: Enterprise Operations & Technology enables Freddie Mac’s business through resilient operations, technology modernization, risk management, and platform innovation. Our teams deliver the capabilities, standards, and tools that help the enterprise operate securely, efficiently, and at scale. Your Impact: Provide senior technical leadership to a maturing cloud platform team by establishing reusable patterns, reference architectures, automation, and implementation standards. Design self-service and self-healing platform capabilities that reduce manual intervention, ticket-driven support, operational delays, and recurring resiliency issues. Deliver AWS-native automation, serverless patterns, infrastructure as code, and code artifacts that create repeatable platform outcomes. Advance AIOps, GenAI, and intelligent automation across