Senior Full-Stack AI Engineer (Agentic AI) (Bengaluru)

Senior Full-Stack AI Engineer (Agentic AI) (Bengaluru)

Company: pubX

Job Location: Bengaluru, Karnataka, India

Employment Type: Full-time

NOTE: This role is a Hybrid role, it requires in person meetups in Bengaluru, India

Why This Role Exists

PubX builds next-generation publisher-first agentic advertising infrastructure. Our AI makes real-time, revenue-critical decisions for digital publishers. Our Bid Intelligence uses machine learning to optimize every programmatic ad auction individually, generating measurable revenue uplift for publishers. Were currently ranked #5 globally in Prebid Analytics Adapter Rankings, and growing.

The problem were solving

Digital publishers leave significant revenue on the table because their tools are are still largely manual, static or simple rule-based. Every ad impression is unique, but most advertising systems treat them the same. PubX's AI analyzes bid-stream data and historical patterns to arrange optimal deals, in near real-time. As a founding member of AgenticAdvertising.org, we're building the next generation of autonomous advertising infrastructure.

What Youll Work On

Tech: Python and/or TypeScript, FastAPI/Node, Kafka/SQS, AWS, Terraform/CDK, AI stack

Design, build, and maintain backend services and APIs (REST/GraphQL/gRPC) that power agentic AI features and core product workflows i.e. MCP and A2A protocols,

Develop web applications that integrate tightly with ML/LLM-driven systems (streaming UX, feedback capture, citations/grounding, stateful sessions),

Build and operate event-driven components using Kafka and message queues (e.g., SQS/RabbitMQ), design asynchronous workflows for long-running agent jobs,

Deploy and operate services on AWS (e.g., ECS/EKS/Lambda, API Gateway/ALB, RDS/DynamoDB, S3), using infrastructure-as-code and secure-by-default patterns,

Improving our reliability, observability, and developer workflows over time, structured logs, metrics, tracing (incl. agent/tool traces), dashboards, alerting, and post-incident reviews.

What Were Looking For

Were looking for an experienced engineer who has worked on production systems and enjoys solving practical problems with AI. Youve likely have:

Strong backend engineering fundamentals: API-first design, data modeling, performance, and security considerations.

Comfortable integrating LLM/ML components into product systems (streaming, async jobs, state, caching, evaluation).

Strong hands-on experience with AI-assisted development workflows in a real codebase (not just demos), including using agents to navigate large repos, apply multi-file changes, and iterate via tests.

Experience building distributed systems with event-driven patterns (Kafka/queues).

Hands-on AWS experience with production operations, monitoring, incident response, and cost-awareness.

You tend to

Make pragmatic decisions balancing speed, quality, cost, and risk trade-offs.

Communicate technical ideas well in writing and conversation to both technical and non-technical audiences.

Write clean, well-tested code with thoughtful abstractions thats easy to extend and operate.

Learn quickly when things are unfamiliar by prototyping, then hardening and documenting what you ship.

Bonus (not required)

Experience with AdTech or other high volume real-time systems

Who This Role Will Suit

This role suits engineers who like a mix of autonomy and collaboration, and who are comfortable working in an environment thats still evolving. Were a distributed team with a growing engineering presence in India, so comfort with async collaboration and clear written communication is important. We use agentic coding tools heavily (e.g. Cursor and Claude Code) to plan, scaffold, refactor, and debug production code, while maintaining strong engineering judgment and ownership of outcomes.

Company Advantages

What We OfferCompetitive salary with meaningful equity

Fully remote, async-friendly working

Supportive, low-ego engineering culture

Budget for learning and professional development

Interview Process

Our process is designed to be practical and respectful.

CV & Profile Review Relevant experience and background

Initial Chat (30 mins) Motivation and role fit

Technical Interview (60 mins) Architecture, design choices, and real scenarios

Practical Exercise + Discussion (60 mins) A small task related to the role

If youre interested in building and shaping real systems in a growing product company, at the forefront of AdTech innovation, wed love to hear from you.

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