Match your resume skills with our AI powered skill match!
Questions interviewers often ask for this role, with sample answers.
Upload your resume and we draft a letter for this exact role, tailored to what it asks for.
You will own the end-to-end vision, strategy, and roadmap for the Forecasting, Deal Management, and Analytics product area. This includes leading the integration of AI capabilities, defining success metrics, and collaborating with cross-functional teams to deliver measurable customer value.
Outreach, founded in 2014, is the only complete agentic AI platform for revenue teams. Outreach infuses agentic AI, conversation intelligence, and assistive AI to power hundreds of use cases across revenue motions. From new logo prospecting to expansions, deal acceleration, driving retention, and forecasting, Outreach AI automates workflows and frees sellers to focus on more strategic conversations and actions. Revenue leaders benefit from connected account visibility, performance insights, and higher forecasting accuracy across every GTM team. World-leading enterprise organisations use Outreach to power their revenue teams, including Databricks, SAP, Siemens, and Verizon.
Outreach is redefining how revenue teams work, and product managers here sit at the center of that work. As a Senior Product Manager within the business unit for Forecasting, Deal Management & Analytics, you will own a product area end to end. This will include the vision, the strategy, the roadmap, and the outcomes for capabilities used every day by sellers and the leaders who run their teams. We are hiring for someone with high product competency and capability that can be adapted into multiple areas of the product. For example, one area we are actively investing in is helping revenue leaders understand and improve seller performance, turning Outreach’s data on real selling behavior into insight, guidance, and coaching that measurably lifts how teams perform.
This role sits within our growing product organization in India, working alongside engineering, design, and data science partners across India, Czechia, and the US.
You will own how AI shows up in your product area: which use cases are worth building, what quality bar those capabilities have to clear, and how you know they are clearing it. This includes evaluation design, guardrails, and playing a hands on role in ensuring AI outcomes.
You will have latitude to decide what gets built and why, with less process than a mature organization but more resources than a small startup. You will be measured on the impact those decisions have on customers and on the business.
\nOwning the vision, strategy, and roadmap for your product area, and being accountable for the outcomes it delivers
Owning the AI application in your product area: identifying and prioritising the use cases worth building, and being willing to say when a problem is better solved without AI
Defining what “good” means for AI-powered capabilities — the evaluation criteria, quality bars, and offline and online measurement that tell you whether a model or agent is genuinely working for customers, and holding the roadmap to those bars
Partnering with data science and ML engineering to take capabilities from experimentation into production, including guardrails, human-in-the-loop design, and the failure modes customers will actually hit
Defining and prioritising the work — making explicit trade-offs on scope, sequencing, and timelines, and explaining the reasoning to partners and leadership
Capturing voice of the customer: leading discovery sessions, running research, and building a first-hand understanding of how revenue teams actually work
Establishing the metrics that define success for your area like adoption, quality, and business impact, and using them to steer the roadmap
Tracking the market, competitive landscape, and customer feedback, and translating them into positioning and roadmap priorities
Working with product marketing, enablement, and finance on launch, positioning, pricing, and packaging
Driving cross-organisational initiatives where your area depends on, or is depended on by, other product teams
7+ years of product management experience building enterprise or B2B SaaS products
Experience launching AI or data products with LLM-powered capabilities, copilots, or agentic workflows, including ownership of their quality after launch
Fluency in modern AI stacks: model integration, context orchestration, prompt design, guardrails, and evaluation frameworks
A demonstrated ability to translate complex AI capabilities into simple product experiences and measurable customer value
Proven ability to work closely with engineering and data scientists to take models from experimentation to production
Comfortable building a business case, working directly with data to test a hypothesis, and making decisions under uncertainty
Customer empathy, and the discipline to keep talking to users rather than reasoning from assumptions
The ability to set a longer-term strategy for your area while driving meaningful short-term impact, and to bring senior leadership and cross-functional partners along with you
Experience with analytics, reporting, or performance-measurement products, or with products that turn behavioural data into recommendations and guidance
Experience building products for go-to-market teams including sales, marketing, revenue operations, or customer success
Experience with conversation intelligence, or with products built on unstructured interaction data
A clear understanding of AI governance, privacy, compliance, and responsible AI principles as they apply to enterprise readiness
Experience working in a distributed product organisation across multiple regions
Stop the endless job search. Our AI finds and applies to the best jobs for you.
Featuring 216,794+ Jobs in Product Manager
Answer easy questions
216,794+ jobs across 15+ categories
Get your best job matches
Only hand-screened, legit jobs
Find a remote job faster
No ads, scams, or junk
“I was the first applicant for a remote marketing position that got listed on the company website the same day I applied. Had an interview within 48 hours!”
— Sarah J.
·
Marketing Manager
★★★★★
Verified
