VisibilityStack helps businesses connect with people who are actively searching for the solutions they offer, both on Google Search and in the new wave of AI-powered search tools.
Our AI agents identify what your audience is looking for, create content that answers those questions, and structure it so Google and AI systems can easily understand and recommend it. We also strengthen your online credibility through strategic backlinks and a strong social presence.
Everything is guided by real-time data. We focus on what works, remove what does not, and keep your content working around the clock. The result is simple: the right people can find you, trust you, and reach out when they need what you offer.
We need a Senior Engineer who ships production code that scales. You'll be the technical anchor building critical infrastructure, solving complex problems, and mentoring junior developers through code reviews and pair programming.
You'll shape our future in four key ways: writing the code that becomes our foundation, being a key voice in engineering hiring decisions, helping establish the processes and patterns everyone follows, and having significant input on product decisions.
What's in it for you:
Own mission-critical systems end-to-end — Your code directly generates customer revenue
Shape product direction — Your technical insights influence product strategy, not just implementation
Learn cutting-edge AI in production — Work with LLMs, vector databases, and agent orchestration at scale
Shape technical decisions and processes — Your input matters on how we build, not just what
Accelerated growth path — As we scale, you choose: become our technical lead or remain a deeply influential IC
Direct founder access — Collaborate on product vision, not just execute specs
Location: Janakpuri, Delhi (Hybrid - Maker's Schedule)
Our Work Philosophy: We follow the Maker's Schedule, not the Manager's Schedule. This means uninterrupted blocks of deep work when you're building, and high-bandwidth collaboration when we're solving problems together.
In Practice:
In-office days: Whiteboard architecture sessions, rapid product iterations, deep dives into product strategy, complex debugging that needs three minds on one problem
Deep work days: Uninterrupted coding from wherever you work best—home, office, or that coffee shop with perfect noise levels
Balance by design: We optimize for both intense collaboration and deep focus
The best technical breakthroughs happen in two modes: intense in-person collaboration where ideas bounce rapidly, and deep solo work where complex problems get solved. We protect both.
Build production systems that handle millions of AI operations daily
Write complex integrations that others can't figure out
Solve scaling problems before they become emergencies
Implement robust error handling and monitoring
Own critical infrastructure components end-to-end
Design APIs that won't need v2 in 6 months
Make pragmatic technical decisions (boring tech when appropriate)
Help establish engineering processes—from code review to deployment
Create patterns and standards other engineers can follow
Lead code reviews that teach, not just critique
Balance shipping speed with technical sustainability
Conduct technical interviews for engineering roles
Design practical coding assessments that test real skills
Provide strong input on hire/no-hire decisions
Partner with founders on technical requirements for roles
Help close strong candidates by selling the technical vision
Pair with junior developers on complex problems
Share knowledge through code reviews and documentation
Unblock teammates when they're stuck
Work directly with founders on technical strategy
Partner with product team on feature design and technical feasibility
Turn product ideas into technical specifications
Work directly with founders on technical strategy
Turn product ideas into technical specifications
5-7 years of software engineering experience
Expert-level Python development skills
Production experience with LLMs (OpenAI, Anthropic, not just prototypes)
Built systems that scaled (and dealt with the failures)
Strong debugging skills—you fix what others can't
API design that makes sense to other developers
Git workflows and collaborative development
Previous early-stage startup experience
Production experience with vector databases (Pinecone, Weaviate, pgvector)
Elasticsearch or search infrastructure expertise
Built revenue-generating AI/ML systems
Experience with high-volume data pipelines
Contributed to open source projects
Informal mentorship or tech lead experience
Backend: Python, FastAPI, PostgreSQL
AI/ML: OpenAI APIs, LangChain, Vector DBs
Infrastructure: AWS, Docker, GitHub Actions
Search: Elasticsearch (evaluating alternatives)
Early employee equity and financial upside
No bureaucracy—your code ships to production
Work on genuinely hard technical problems
Learn from and contribute to cutting-edge AI systems
Clear growth path as the team scales