Forward Deployed AI Solutions Engineer

About the role The Staff Forward Deployed Solutions Engineer will work directly within a business domain (e.g., Commercial, Clinical Operations, Lab Operations, Sales & Marketing, Customer Experience etc.). In your role, you’ll find opportunities for enhancing efficiency and productivity by looking for workflows which can be executed 10–100x faster or more often than a human team could using AI agents, integrations and other patterns. You will build, deploy, and run them in production. You report into the central AI & Automation team, partner directly with domain leadership on priorities, and bring patterns back so the whole company compounds. Find the leverage in your domain Map the workflows in your domain — the ones running today, and the ones that don’t exist yet because they weren’t feasible without agents or automation tools. Identify the step-change opportunities: where AI, ML, or automation unlock throughput, coverage, or speed. Build the business case, quantify projected impact, and align with domain leadership on priorities. Design the future-state workflow Map structured and unstructured data flows across the systems involved (CRM, ERP, ticketing, document stores, internal tools, external SaaS). Define the target workflow: what the agent does, what the human does, and where they hand off. Figure out what context the agent or model needs to do the work well — and how to get it there reliably (retrieval, grounding, tool access, memory). Design human-in-the-loop checkpoints so review adds value without becoming the bottleneck. Build and connect the systems Stand up agents and automation pipelines using the organization’s approved AI platforms and frameworks. Connect agents to business systems — via MCP servers, APIs, webhooks, CLIs, and skills — within the guardrails set by IT and security. Configure tools, prompts, context, and retrieval pipelines so agents perform reliably on real work, not just in demos. Handle integration gnarliness:

About the role The Forward Deployed Solutions Engineer will work directly within a business domain (e.g., Commercial, Clinical Operations, Lab Operations, Sales & Marketing, Customer Experience etc.). In your role, you’ll find opportunities for enhancing efficiency and productivity by looking for workflows which can be executed 10–100x faster or more often than a human team could using AI agents, integrations and other patterns. You will build, deploy, and run them in production. You report into the central AI & Automation team, partner directly with domain leadership on priorities, and bring patterns back so the whole company compounds. Find the leverage in your domain Map the workflows in your domain — the ones running today, and the ones that don’t exist yet because they weren’t feasible without agents or automation tools. Identify the step-change opportunities: where AI, ML, or automation unlock throughput, coverage, or speed. Build the business case, quantify projected impact, and align with domain leadership on priorities. Design the future-state workflow Map structured and unstructured data flows across the systems involved (CRM, ERP, ticketing, document stores, internal tools, external SaaS). Define the target workflow: what the agent does, what the human does, and where they hand off. Figure out what context the agent or model needs to do the work well — and how to get it there reliably (retrieval, grounding, tool access, memory). Design human-in-the-loop checkpoints so review adds value without becoming the bottleneck. Build and connect the systems Stand up agents and automation pipelines using the organization’s approved AI platforms and frameworks. Connect agents to business systems — via MCP servers, APIs, webhooks, CLIs, and skills — within the guardrails set by IT and security. Configure tools, prompts, context, and retrieval pipelines so agents perform reliably on real work, not just in demos. Handle integration gnarliness: auth, schema

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview Instacart's Enterprise Solutions team is building a first-of-its-kind business: embedding directly with enterprise retail and CPG partners to design, sell, and deliver AI-powered solutions at scale. We are a small, senior, field-first pod — part startup, part consultancy — defining the playbook as we go. As a Forward Deployed Engineer, you are Instacart's hands-on technical presence inside enterprise customer environments. You will sit inside retailers' and partners' ecosystems, understand their infrastructure, and build agentic AI solutions on top of it. As part of your mission, you will brainstorm with partner technical leaders and collaborate on solution designs that deliver value while remaining compatible with existing environments and infrastructure. You will also collaborate closely with Instacart R&D's team, informing platform evolution

About Artefact Artefact is a next-generation data and AI consulting firm dedicated to accelerating the adoption of data and AI to create measurable business impact across the full enterprise value chain. We sit at the intersection of consulting, data science, AI technologies, data engineering, and digital transformation. We do not just advise — we build, implement, and deliver results our clients can measure. Our teams bring together consultants, data scientists, data engineers, AI engineers, analysts, and digital experts to solve complex business challenges with pragmatic, production-ready solutions. As Artefact continues to grow globally, we are building a team of entrepreneurial data and AI talent who can help clients move beyond experimentation and into scalable, governed, value-generating AI adoption. The Role Artefact is looking for a Senior Deployed AI Engineer specialized in Gemini Enterprise and the Google AI stack: an engineer who works embedded with our clients and takes AI products from idea to production. You will design and build the interfaces, services, and agentic systems at the heart of our client work, such as conversational applications over enterprise data, multi-step agents that automate business workflows, and the retrieval and data pipelines that support them. You will own your components end to end: the front end, the service behind it, the data and retrieval pipelines feeding it, the deployment, and the evaluations proving it works. This role combines deep, certified expertise in Google's enterprise AI stack (Gemini models, Vertex AI, and the Gemini Enterprise agent platform) with the ability to deliver end to end. Beyond your platform specialization, you will be expected to work confidently across the full delivery lifecycle — full-stack development, data engineering, cloud infrastructure, evaluation, and client communication. You will work closely with our clients, with direct exposure from the start, and you will support the professional

HackerRank helps companies like NVIDIA, Amazon, and Microsoft hire and upskill the next generation of developers based on skills, not pedigree. Our platform is trusted by over 2,500 of the world’s most innovative companies to build strong engineering teams ready for what’s next. Software has entered an era where humans and AI build side by side. As this shift accelerates, the definition of strong technical talent is changing. We give companies better ways to identify and invest in next-generation skills. People at HackerRank care deeply about the impact of their work and sweat the small details so our customers can be wildly successful with products they genuinely love to use. We move with urgency and believe great outcomes come from high standards. About the Role HackerRank is scaling its Forward Deployed Engineering (FDE) function globally. We are hiring a Director, Forward Deployed Engineering (Global) to set the strategy, standards, and execution bar for this team. This is a hands-on leadership role. You will lead the global FDE function, directly manage FDEs in the U.S., and partner closely with regional GMs in EMEA and APAC. What you’ll do Lead, coach, and grow a team of FDEs that lead customer engagements (pre- and post-sales) to define and deliver solutions. Partner with Sales, Product, Engineering, and Customer Success to shape solutions that solve real customer problems. Work with Product and Engineering to incorporate customer-specific solutions into the product roadmap. Provide hands-on technical leadership across APIs, integrations, and platform capabilities. Elevate how we run demos, proofs of concept, and onsite engagements. Build repeatable playbooks, delivery standards, and best practices to move fast at scale. Who you are A seasoned technical leader with 8+ years in engineering, solutions engineering, or technical delivery, and 2+ years leading high-performing technical teams. Obsessed with operating alongside the team, reviewing designs, challengi

Work directly with clients to turn business problems into production-ready AI solutions. The Role As an AI Engineer , you’ll work directly with our clients to understand business problems and turn them into working AI solutions. Combining hands-on engineering with a consulting mindset, you’ll take ideas from initial requirements through prototyping, demonstration, iteration, and deployment. This is a client-facing, forward-deployed engineering role. You’ll work closely with business stakeholders to understand what they are trying to achieve, help shape the right solution, and then build it. You’ll need to be as comfortable discussing requirements and demonstrating a solution with business teams as you are writing Python and developing AI agents. You won’t be tied to a single technology or environment. You’ll work across different client architectures and platforms, adapting to environments such as Snowflake and Databricks and selecting the right approach for each use case. Success in your first few months will mean building strong relationships with business stakeholders and successfully delivering an AI use case from business problem through to a working solution. What You’ll Do Work directly with business stakeholders to understand their problems, uncover requirements, and translate them into practical AI solutions. Design, build, test, demonstrate, and deploy AI agents and agentic solutions that solve real business problems. Take ownership of hands-on engineering across the solution lifecycle, from rapid prototypes through iteration and deployment. Work across different client technology environments and platforms, adapting your approach to the architecture, data, and tools available. Demonstrate solutions to business stakeholders, gather feedback, and collaborate across product, data, technology, and business teams to continuously improve what you build. What We’re Looking For 2+ years of relevant software, data, or AI engineering experience, with hands-o