[![Image]() Meet Jobicy Copilot — free AI autofill for job applications + remote job alerts ›](#) [All remote jobs](https://jobicy.com/jobs.md)Open role[![Liftoff logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/c47aea9f-221.png)](https://jobicy.com/company/liftoff.md)Remote opportunity at[Liftoff](https://jobicy.com/company/liftoff.md) # Senior Gen AI Software Engineer Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/liftoff.md)Share12 Sep 2026Published34Listing views1Application actions12 Oct 2026Apply before Opportunity details ## About this role. AI SummaryLiftoff seeks a senior software engineer to own generative-AI product capabilities from discovery and rapid prototyping through production rollout, measurement, and iteration. The role combines Python services and data pipelines with TypeScript and React user experiences, emphasizing reliable agentic workflows grounded in campaign and customer data. The engineer will establish evaluation, observability, safeguards, tool interfaces, state management, and human-review boundaries for LLM-powered products. This high-ownership position also requires close collaboration with product and customer-facing teams, sound product judgment, and mentorship of other engineers. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis is a senior, end-to-end AI engineering role requiring at least eight years of relevant experience and demonstrated delivery of production LLM products. Success depends on solving ambiguous technical and product problems while ensuring reliability, evaluation rigor, security, cost control, and measurable business impact. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job medianHighly competitive$240,500US market range$190k–$280k0$308k AI insightThe disclosed annual base-salary range is $211,000-$248,000 for approved states outside major listed markets and $230,000-$270,000 for the SF Bay Area, Los Angeles/Orange County, NYC, and Seattle. Using the overall disclosed range, the job-offer median is $240,500 annually. A competitive US-market base-salary estimate for a senior generative-AI software engineer is approximately $190,000-$280,000 annually; equity and benefits are additional and are not included in this estimate. ## Core skills Skills and capabilities most closely associated with this opportunity. [Generative AI](https://jobicy.com/jobs?search_keywords=Generative%20AI.md)[LLM Applications](https://jobicy.com/jobs?search_keywords=LLM%20Applications.md)[Agentic Workflows](https://jobicy.com/jobs?search_keywords=Agentic%20Workflows.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[TypeScript](https://jobicy.com/jobs?search_keywords=TypeScript.md)[React](https://jobicy.com/jobs?search_keywords=React.md)[API Design](https://jobicy.com/jobs?search_keywords=API%20Design.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[AI Evaluation](https://jobicy.com/jobs?search_keywords=AI%20Evaluation.md)[Production Observability](https://jobicy.com/jobs?search_keywords=Production%20Observability.md) Sample interview questionsDescribe an LLM-powered product you took from prototype to production. How did you determine it was ready to launch?I would explain the customer problem, prototype scope, and success metrics first. I would then describe building an evaluation set from realistic workflows, adding automated quality and safety checks, conducting human review, and defining launch thresholds for accuracy, latency, cost, and failure rates. I would also cover staged rollout, instrumentation, and the iteration process after release. How would you design an agent that analyzes campaign-performance data and recommends next actions? I would start by defining narrow user tasks and the decisions the agent may support, then provide governed tools for retrieving approved campaign, creative, and performance data. The agent would return structured outputs with evidence, confidence or uncertainty signals, and recommended actions, while requiring human approval for consequential changes. I would include permissions, audit logs, fallbacks, state management, and evaluation scenarios covering incomplete, conflicting, and stale data. What methods do you use to evaluate quality and reliability in a generative-AI feature? I use a layered approach: offline task-based evaluation sets, deterministic schema and tool-use tests, model-judged checks calibrated against human labels, and targeted human review. In production, I monitor adoption, task completion, correction rates, user feedback, latency, token cost, tool failures, and safety incidents. I treat evaluation as a continuously maintained product asset rather than a one-time release gate. How do you decide whether to use a traditional software solution, an LLM, or a hybrid approach? I first assess whether the task has deterministic rules, stable inputs, and low ambiguity; those are usually best served by conventional software. I use an LLM where language understanding, synthesis, flexible reasoning, or unstructured information creates meaningful user value. In a hybrid design, deterministic systems enforce permissions, business rules, validation, and side effects, while the model handles interpretation and generates structured recommendations. Tell us about a time you worked through substantial ambiguity with cross-functional partners. I would describe how I converted a broad business request into observable user workflows, assumptions, and measurable outcomes through interviews and rapid prototypes. I would explain how I shared tradeoffs clearly with technical and non-technical stakeholders, used evidence from experiments to prioritize the next step, and changed direction when the results challenged the original plan. The outcome would demonstrate both ownership and collaborative decision-making. Liftoff is a leading AI-powered performance marketing platform for the mobile app economy. Our end-to-end technology stack helps app marketers acquire and retain high-value users, while enabling publishers to maximize revenue across programmatic and direct demand. Liftoff’s solutions, including Accelerate, Direct, Monetize, Intelligence, and Vungle Exchange, support over 6,600 mobile businesses across 74 countries in sectors such as gaming, social, finance, ecommerce, and entertainment. Founded in 2012 and headquartered in Redwood City, CA, Liftoff has a diverse, global presence. Join Liftoff as a Senior Gen AI Software Engineer and help shape the future of ad tech. As a key member of our Gen AI team, you’ll design and build AI-powered products for our demand-side business, helping teams turn complex data into better decisions and meaningful customer growth. You’ll work across the stack, building intelligent systems and data pipelines in Python, alongside the TypeScript and React experiences that bring those capabilities to users. You’ll partner closely with product, engineering, and customer-facing teams to identify high-impact opportunities, move quickly from prototype to production, and continuously improve what you ship. This is a hands-on role for an engineer who enjoys working at the intersection of AI, product, and software engineering. You’ll help define how Liftoff applies modern AI to real business problems, balancing experimentation with the judgment and engineering discipline needed to build useful, reliable products. This role is ideal for an engineer who thrives in ambiguity, enjoys experimenting with new technology, and is motivated by turning promising AI capabilities into products that create real value. You’ll tackle complex problems, validate new approaches, and drive meaningful improvements across Liftoff. WHAT YOU’LL DO * Own generative AI product capabilities end to end, from understanding user workflows and prototyping an approach through implementation, rollout, measurement, and ongoing improvement. * Rapidly prototype and validate AI solutions, using focused experiments to test user value and technical feasibility, then turn what works into production-ready capabilities. * Build agentic workflows that can reason over campaign, customer, creative, and performance data, use well-defined tools, produce structured results, and hand control back to a person when appropriate. * Partner closely with decision makers and subject matter experts to understand their workflows, constraints, and business context, then integrate AI agents into daily work in practical and useful ways. * Design how AI systems access and use relevant information, including the data, tools, and instructions needed to produce useful grounded results. * Build the systems that make AI workflows reliable in production, including tool use, state management, failure recovery, and appropriate boundaries for human review. * Define clear, testable interfaces between models and software so uncertain model behavior can be handled safely within dependable product systems. * Develop evaluation systems that measure whether AI features accomplish the intended task, using realistic examples and an appropriate combination of automated checks and human judgment. * Build the instrumentation needed to understand quality, adoption, business impact, latency, cost, and failure modes in production. * Apply appropriate safeguards for customer data, system access, and high-impact workflows. * Build the Python services and TypeScript and React interfaces that turn these capabilities into cohesive products for customer facing teams. * Evaluate new models and techniques pragmatically, adopting them when they materially improve product quality, capability, speed, or cost. * Mentor other engineers and help establish shared practices for designing, testing, and operating AI-powered products. WHO YOU ARE * Minimum Bachelors Degree and 8 yrs of relevant experience. * You are a seasoned software engineer who has built and operated meaningful production products, ideally including zero-to-one work spanning backend services, data, and user interfaces. * You have shipped LLM-powered or AI-assisted products beyond a demo and understand the practical challenges of reliability, context, tool use, provider changes, latency, cost, and changing model behavior. * You are highly proficient in Python and comfortable working in TypeScript and React, with strong fundamentals in API design, data modeling, SQL, and testing. * You understand how to build the broader system around a model, including its data, tools, instructions, permissions, feedback loops, and measures of quality. * You can define success criteria, investigate failures, and use testing, feedback, and production signals to improve AI experiences over time. * You exercise strong product and engineering judgment, choosing when a problem calls for traditional software, an LLM-powered approach, or a thoughtful combination of both. * You communicate complex technical ideas clearly and collaborate effectively with domain experts and non-technical partners. * You are comfortable working through ambiguity, making informed decisions with incomplete information, and changing direction when evidence shows a better path. * You are a lifelong learner with strong but flexible opinions, and you thrive on giving and receiving constructive feedback. ### Helpful, but not required * Experience as an early engineer, startup founder, or in a similarly high-ownership environment where you moved quickly from ambiguous problems to shipped products. * Experience with advertising technology, campaign optimization, performance marketing, analytics products, or other data-rich B2B software. Location: The preferred location for the role is in Pacific Standard Time Zone. This role is eligible for full-time remote work in one of our entities: CA, CO, ID, IL, FL, GA, MA, MI, MN, MO, NJ, NV, NY, OR, PA, TX, UT, and WA. We are a remote-first company with US hubs in Redwood City, Los Angeles, and New York City. Travel Expectations: We offer several opportunities for in-person team gatherings, including but not limited to project meetings, regional meetups, and company-wide events. We expect our employees to attend these gatherings at least once per quarter. These gatherings provide essential opportunities for collaboration, communication, and team building. Compensation: Liftoff offers all employees a full compensation package that includes equity and health/vision/dental benefits associated with your country of residence. Base compensation will vary based on the candidate’s location and experience. The following are our base salary ranges for multiple levels: * SF Bay Area, Los Angeles/Orange County, NYC, Seattle: $230,000 – $270,000 * All other cities and towns in our approved states: $211,000 – $248,000 #LI-VM1 Liftoff offers a fast-paced, collaborative, and innovative work environment where employees are empowered to grow and make an impact. We’re shaping the future of the mobile app ecosystem—join us and help accelerate what’s next. Liftoff’s compensation strategy includes competitive salaries, equity, and benefits designed to support employee well-being and performance. We benchmark compensation based on role, level, and location to ensure fairness and market alignment. Benefits may include medical coverage, wellness stipends, and additional perks based on your country of residence. Liftoff is an equal opportunity employer. We are committed to creating an inclusive environment for all employees and applicants regardless of race, ethnicity, national origin, age, marital status, disability, sexual orientation, gender identity, religion, veteran status, or any other characteristic protected by applicable law. Agency and Third Party Recruiter Notice: Liftoff does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or Recruiting Team. All candidates must be submitted via our Applicant Tracking System by approved Liftoff vendors who have been expressly requested to make a submission by our Recruiting Team for a specific job opening. No placement fees will be paid to any firm unless such a request has been made by the Liftoff Recruiting Team and such a candidate was submitted to the Liftoff Recruiting Team via our Applicant Tracking System. 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