{"id":203679,"url":"https://alion.io/job/squadstack-forward-deployed-engineer","title":"Forward Deployed Engineer","company":{"id":171193,"name":"Squadstack","domain":"squadstack.ai","url":"https://alion.io/company/squadstack","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":{"grade":"B","score":83,"open_postings":10,"ghost_share":0,"stale_share":0.7,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-28T05:59:10Z"}},"role":"Solutions","role_family":"Solutions","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Noida, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"JavaScript","optional":false},{"name":"LLM","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Context Engineering","optional":true}],"status":"live","first_seen_at":"2026-07-16T04:47:48Z","employer_posted_date":"2026-07-16","last_verified_at":"2026-10-29T01:30:23Z","board_verified":true,"closed_at":null,"days_open":104,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":104},"description":"About the role\nAs aForward Deployed Engineer at SquadStack.ai, you’ll work on building and evolving production-grade Voice AI systems that customers actively use.\nYou’ll operate close to real deployments - identifying gaps surfaced by live usage, designing solutions, and shipping them into production. Some work moves fast; some work is planned and iterative. What matters is that priorities are driven by real customer outcomes, not by work defined quarters in advance.\nYou’ll leverage the SquadStack platform to configure, extend, and build AI-native workflows, while writing production-quality code where needed. You’ll work in a small pod alongside Customer Success and AI PM partners, owning technical execution end-to-end.\nThis role sits at the intersection of engineering, product, and customer reality - with a strong emphasis on code quality, system reliability, and long-term leverage over one-off fixes.\n\nApply even if you’re only 70% sure. The conversation itself is valuable.\nWhat you'll do\nYou’ll work in a small pod (CSM / AI PM handles customer communication; you handle technical execution), solving problems that block customer success but aren’t yet on the product roadmap.\nYour engineering work includes:\nBuilding custom integrations, tools, and AI workflows that unblock customer needs\nDesigning and refining AI prompts, RAG systems, and LLM-based solutions\nWriting production-quality code (Python / JavaScript) with the same standards as core engineering\nDeciding whether solutions should remain custom, become reusable, or move into the core product\nCollaborating with core engineering teams to upstream learnings and reduce future friction.\nWhat you will not do:\nRun customer calls\nOwn accounts\nChase stakeholders\nDo repetitive support work\nThis is NOT solutions engineering\nYou do not deliver one-off scripts and move on\nEvery solution is evaluated on leverage:\nCan this be reused?\nCan this become a product primitive?\nCan this eliminate future manual work?\nCustom work is acceptable only if the business makes sense, or it is experimental, where we’d learn something new.\nStrong solutions frequently get upstreamed into:\nCore platform capabilities\nReusable internal tooling\nProduct roadmap items owned by core engineering\nYour success is measured by reduced future friction - not by how many customers you personally unblock.\nCode quality: Same high bar\nTechnical difficulty: Often harder - real-world problems are messier and more near-term in nature than planned roadmaps\nTwo engineering tracks - both valuable:\nCore Engineering:\nProduct Roadmap\nRoadmap and sprint-driven\nDeep, well-scoped, long-lived\nPlatform & system optimisation\nSlower, abstracted\nPlatform Abstractions & scalability\nCustomer Impact (This Role):\nDay-to-day customer usage & success signals\nSignal-driven; flexible planning\nBroad, evolving, discovery-heavy\nUnblocking + generalising into scale\nImmediate, real-world\nReduction of future friction & repeat issues\nBoth are real engineering. Both lead to staff or lead roles. Both are equally respected.\nWhy ambitious engineers choose this role\n Unmatched learning velocity:\nBuild with cutting-edge AI (LLMs, prompt engineering, RAG) in production\nLearn what actually makes products succeed in real markets\nDevelop full-stack skills alongside business judgment\nReal Autonomy:\nChoose your own tools and approaches\nShip when ready - not when a sprint ends\nDirect influence on the product roadmap & org metrics via real usage\nCareer acceleration:\nEngineers from this track commonly become:\nProduct Engineers who can both build and prioritise\nTechnical Leads who deeply understand customer reality\nFounding Engineers or CTOs at startups with a complete skill stack\nImmediate impact:\nDirect feedback from real usage\nClear line from your work to business outcomes\nWhat we’re looking for\nTechnical baseline:\nStrong programming fundamentals (Python / JavaScript preferred, but talent > language)\nComfort with ambiguity and incomplete requirements\nCuriosity about AI / ML in production (expertise is a bonus, not a requirement)\nMindset fit:\nOwnership: Takes end-to-end responsibility for outcomes, not just tasks; drives problems to resolution even across unclear boundaries.\nPragmatic: Focused on solutions that work now\nCurious: Wants to understand the “why” behind problems\nEntrepreneurial: Treats technical problems as business problems\nCommunicative: Can translate technical decisions into a business context\nAI Native: Exposure to AI systems or prompt & context engineering.\nShould I apply?\nYES, if you:\nWant to work on AI-native products at the frontier\nEnjoy variety - no two weeks look the same\nCare about understanding the “why” behind what you build\nPrefer building solutions over strictly following specs\nI am curious about how engineering decisions affect business outcomes\nMAYBE NOT, if you:\nPrefer predictable, tightly defined work\nDislike exposure to business or customer context\nNeed detailed specs to be productive\nPrefer large teams over small, autonomous pods\nWant to avoid ambiguity or rapid context-switching\nDay-to-day reality\nNo two weeks look the same, but a typical flow might look like this:\nMonday: Pod sync to review customer progress and technical blockers. One issue stands out - a workflow the product doesn’t fully support yet.\nTuesday: Prototype a solution (integration, tool, or AI workflow). Loop in core engineering early if it looks reusable.\nWednesday: Refine the solution - edge cases, AI prompt behaviour, reliability. Decide whether this should remain custom or be generalised.\nThursday: Ship to production. Monitor real usage. Iterate quickly if needed.\nFriday: Share learnings, move on to the next.\nQuick Check?\nFreedom level: High\nBureaucracy: Low\nLearning curve: Steep\nImpact visibility: Immediate and measurable\nLogistics\nLocation: Noida\nCompensation: Competitive!\nJoining: ASAP!\nWhy should you consider us seriously?\nWe believe that long-term, people over product and profits, prioritize culture over everything else.\nWe are a well-balanced team of experienced entrepreneurs and are backed by top investors across India and Silicon Valley (Chiratae Ventures, Blume Ventures, Abstract Ventures, Emergent Ventures; Senior execs at Google, Square, Genpact & Flipkart; Co-founders of Infosys, Snapdeal, Slideshare, Zomato, etc.)\nFreedom and Responsibility \nEntrepreneurial Team \nExponential Growth \nHealthcare (Physical & Mental Wellness) \nPlease Note:\nSquadStack is committed to a diverse and inclusive workplace. 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