Discovr AI
https://getdiscovr.aiAbout
Discovr AI is an agentic, AI-native creator advertising platform that helps brands and agencies plan, execute, and measure influencer campaigns with speed, control, and repeatable performance. We automate the campaign lifecycle—from briefs and creator selection to approvals, QA, and reporting—so teams can scale creator programs without scaling headcount. Built for enterprise workflows, Discovr AI brings structured processes, visibility, and measurable outcomes to creator-led advertising
Tech stack
NodeJS (Node.js)
Go Programming (Golang)
PythonCandid answers by the company
Discovr AI is an agentic, AI-native advertising platform that automates the entire influencer marketing lifecycle for brands and agencies. Based in Mumbai, it accelerates campaign creation from creator discovery and onboarding to tracking and reporting, allowing companies to scale influencer programs without increasing headcount.
Company social profiles
Jobs at Discovr AI
NodeJS (Node.js)Go Programming (Golang)
React.jsAbout the company
We’re building an agentic, AI-native infrastructure for creator advertising, automating the end-to-end campaign lifecycle (brief → creator selection → outreach/follow-ups → approvals → delivery QA → reporting) with enterprise-grade workflows, reliability, and measurable outcomes.
The role
As a Full Stack Engineer, you will design and build core systems across backend, product surfaces, integrations, and LLM-powered automation. You’ll take high ownership, move quickly, and set strong engineering foundations as we scale. This is an in-office role in Mumbai.
Location: Mumbai (In-office, 5 days/week)
Type: Full-time
Experience: 5 + years (flexible; we value ownership and shipping ability over years)
Reports to: Founder/CEO (partners closely with PM)
Traction: Working with large enterprises and managing seven-figures per month in influencer spend
What we’re looking for
Must-haves
- Strong software engineering fundamentals with a track record of shipping production systems
- LLM/AI experience is required: you’ve shipped LLM-powered features to users (agents/tool-calling/RAG/evals/guardrails—at least some of these)
- Comfortable owning end-to-end systems (backend + APIs + data + enough frontend to deliver outcomes)
- Strong practical skills in at least one stack such as Node.js / TypeScript / Go
- Experience with:
○ REST APIs, webhooks, auth (JWT/OAuth basics), role-based permissions
○ production debugging (logs/metrics/traces), handling edge cases, writing tests
○ core data stores (e.g., Postgres) and common cloud primitives
- High ownership, speed, and strong product intuition
- Mumbai in-office availability (or immediate relocation)
Nice to have
- Experience with workflow-heavy products: marketplaces, fintech, logistics, AdTech, B2B SaaS
- SQL comfort and familiarity with analytics pipelines / event schemas
- Multi-tenant enterprise features: audit logs, data isolation, SSO (now or later)
What you’ll do
Build core product workflows (enterprise-grade)
- Implement robust workflow/state systems (approvals, retries, exceptions, audit logs)
- Build internal tooling/admin panels to scale operations and reduce manual effort
- Deliver customer-facing dashboards and reporting experiences
Build and ship LLM/agent capabilities (must-have)
- Implement agentic workflows using LLMs + tools (retrieval, structured actions, messaging sequences, QA checks)
- Build guardrails: policy checks, human-in-the-loop review points, safe fallbacks, and prompt/tool versioning
- Create evaluation & monitoring: offline test sets, automated checks, and online metrics to maintain output quality over time
Integrations + platform plumbing
- Build and maintain integrations via APIs/webhooks
- Own instrumentation: event tracking, data quality checks, and reporting accuracy
- Implement permissions, access controls, and reliability patterns appropriate for enterprise usage
Engineering culture + velocity
- Ship frequently with high quality (tests, code review, CI, observability)
- Collaborate closely with product on discovery, prioritization, and customer feedback
- Contribute to hiring and mentoring as the team grows
NodeJS (Node.js)About us
We’re building an agentic, AI-native platform for creator advertising — automating the campaign lifecycle (brief → creator selection → outreach/follow-ups → approvals → delivery QA → reporting).
The role
We’re hiring a Product Manager who can code and can drive product end-to-end while working extremely closely with the engineering team. This is a builder role: you’ll design agent workflows, run tight execution, and help shape the product foundation for scale. This is an in-office Mumbai role.
Location: Mumbai (In-office, 5 days/week)
Type: Full-time
Experience: 2–6 years (flexible for exceptional builders)
Reports to: Founder/CEO
Works with: Engineering (small team), and later Design/Data/Ops Traction: Working with large enterprises and managing seven-figures per month in influencer spend
What we’re looking for
Must-haves
- 2–6 years shipping software products (years flexible if you can prove ownership)
- Strong technical fluency end-to-end:
○ APIs/webhooks, auth basics, event tracking & analytics
○ ability to reason through edge cases, reliability, and scalability tradeoffs
- Can code (proficient in Python/TypeScript/JavaScript/Go) and comfortable doing hands-on work when needed
- Demonstrated ability to run user interviews and convert insights into shipped outcomes
- Proven shipping in fast cycles with real outcomes/metrics
- High ownership, crisp communication, strong execution leadership
- Mumbai in-office availability (or immediate relocation)
Nice to have
- Built LLM/AI features with real users (prompts + tools + evaluation/guardrails)
- Experience with marketplaces, AdTech/measurement, creator/influencer products, B2B SaaS
- SQL comfort and familiarity with analytics/debugging production systems
What you’ll do
Customer discovery & user interviews (core part of the job)
- Do weekly user interviews with enterprise marketing teams, agencies, and creators
- Turn messy feedback into clear product bets, workflows, and experiments
- Build strong product intuition by staying close to users and real campaign execution
- Validate new features with rapid prototypes and structured feedback loops
Build the agentic AI product
- Design agent workflows: what the agent does, what humans approve, and how exceptions escalate
- Define tool usage for the agent (retrieval, matching, messaging sequences, QA checks)
- Specify evaluation + guardrails (quality metrics, fallbacks, audit logs, safety/brand checks)
Own core platform workflows (enterprise-grade)
- Own campaign workflow states, approvals, permissions, and internal ops tooling
- Drive integrations (APIs/webhooks) and reliable execution paths
- Define instrumentation (event schema) and ensure reporting accuracy + trust
Drive execution with engineering
- Write specs engineers can build from (flows, acceptance criteria, edge cases)
- Run sprint planning, prioritization, release readiness, QA
- Make scope tradeoffs quickly and maintain a weekly shipping cadence
Hands-on building (coding)
Depending on your strengths, you may:
- build internal tools/admin screens, scripts, prototypes, integrations, data utilities
- write quick POCs for agent workflows, tool definitions, or evaluation harnesses
- help debug production issues using logs/SQL
What success looks like
- Weekly cadence of user interviews → clear insights → shipped improvements
- MVP agent workflow shipped with measurable time savings + quality controls
- Reduced manual ops per campaign through automation + internal tooling
- Trusted reporting and instrumentation (customers trust the numbers)
- Consistent weekly shipping cadence and strong engineering throughput
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