Description :

What to expect at MediaMint-

We love people who define their surroundings and who are constantly looking to learn new things. We value honesty and integrity above all. We love people who are honest, self-aware and intent on bettering themselves each day. If you love growth - professional and personal, then MediaMint is most likely the place for you!

What do we do :

MediaMint is an AI-powered Revenue Operations services company dedicated to accelerating innovation and revenue growth for platforms and publishers worldwide. Our mission is to enhance operational efficiency, scalability, customer satisfaction, and data-driven insights through advanced technology, automation, and AI capabilities. We serve industry leaders across AdTech, Consumer, CTV, Publishing, and Retail.

Job Description :

You own the implementation end-to-end : discovery through production scale. You'll map client workflows, architect agent-based solutions on MediaMint AI, ship them live, and prove ROI with hard numbers. You also lead a team of implementation engineers setting technical standards, unblocking production issues, and turning one-off wins into reusable playbooks. This is a hands-on leadership role : you architect, you code, you ship, you lead.

What You'll Do :

- Process Discovery & Value Sizing Run workshops and shadow operations to build current-state maps (SIPOC, BPMN, swimlanes). Identify bottlenecks, SLA risks, error sources, and compliance constraints. Size every opportunity with baselines (time, cost, error rate) and target outcomes.

- Solution Architecture Translate client workflows into MediaMint AI's modular agent stack : data ingestion, enrichment, decisioning, QA, notifications.

- Define guardrails, exception paths, human-in-the-loop checkpoints, and prompt strategies. Own the technical design from schema mapping through API integration.

- Hands-On Engineering Build, configure, and deploy AI agents and automation pipelines using Python.

- Implement RAG patterns, prompt engineering, and LLM orchestration via LangChain, AutoGen, or CrewAI. Integrate with OpenAI API, Azure OpenAI, REST APIs, and third-party systems.

- Debug agent logic, data flows, and integration failures in production.

- Pilot-to-Scale Execution Scope tight pilots with clear exit criteria. Configure agents, prompts, rules, and integrations. Coordinate UAT with Service Delivery and client SMEs.

- Cut over to production with dashboards, SLIs/SLOs, runbooks, and tiered support paths.

- Team Leadership Lead a team of implementation engineers. Set coding standards, review architectures, and conduct design discussions.

- Mentor engineers on agentic patterns, debugging techniques, and client communication.

- Ensure the team delivers reliably under pressure.

- Client-Facing Technical Ownership Handle technical communication with clients directly.

- Translate business needs into engineering plans and engineering constraints into business language.

- Run weekly steering, RAID logs, and OKR tracking.

- Platform Feedback Loop Convert field learnings into platform requirements and reusable templates.

- Influence the MediaMint AI roadmap with quantified impact data and voice-of-customer insights.

What You Must Bring :

- 10+ years in software engineering with hands-on AI/automation implementation experience and at least 2 years leading a technical team.

- Production experience building LLM-powered applications, AI agent systems, or agentic workflow pipelines.

- Strong Python backend skills : REST APIs, third-party integrations, API authentication (OAuth, tokens, API keys).

- Working knowledge of AI frameworks (LangChain, AutoGen, CrewAI) and platforms (OpenAI API, Azure OpenAI).

- Proven expertise in process discovery and workflow redesignable to map a client operation and architect an automated replacement.

- Experience with automation tools (Playwright, Selenium, or equivalent).

- Strong debugging instincts : diagnosing agent logic failures, data flow issues, and integration breakdowns in production.

- Clear, concise communicatorcomfortable running client workshops, steering meetings, and technical reviews.

Bonus Points :

- Domain experience in AdTech/MarTech/RevOps (campaign setup, pacing, QA, attribution, trafficking, reporting).

- Process improvement credentials (Lean Six Sigma, BPMN) or change management experience (Prosci/ADKAR).

- Exposure to data tooling (Airflow, dbt, Snowflake, BigQuery) and CRM/ticketing systems (Salesforce, Jira, Zendesk).

- Experience with cloud infrastructure (AWS/Azure/GCP), containers (Docker, Kubernetes), and CI/CD pipelines.

- Background in quality frameworks for AI : guardrails, red-teaming, bias detection, and latency SLAs.