Full-Stack Engineer

MetAntz; Bengaluru; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

MetAntz is seeking an engineer to build AI agents in production, close to customer workflows. You will write Go and Python, design schemas, build evals, and present solutions to senior executives at enterprise clients within weeks.

You’ll own end-to-end production systems from discovery to deployment, balancing speed and reliability while collaborating with global teams and multi-tenant SaaS environments. A strong communicator with customers is essential.

Qualifications

• 5+ years building and scaling end-to-end production systems.
• Strong backend fundamentals in Python and Go.
• Experience solving in fast-changing, ambiguous environments.
• Builder mindset with high personal agency.
• Comfort with direct customer interaction.
• Clear, direct communication to technical and non-technical audiences.

Responsibilities

• Design and ship production agents embedded in Teams, Slack, intranets, voice lines, and email; integrate with SAP, ServiceNow, Workday and other systems.
• Own the full lifecycle: discovery, build, eval, launch, and ongoing reliability improvements.
• Work directly with leaders at global enterprises to extract processes and decide what should be an agent or a workflow.

Skills

5+ years engineering experience

Python

Go

Backend fundamentals

Customer communication

Problem solving

Ambiguity handling

Agency / initiative

Job description

About MetAntz

MetAntz has one of the most advanced GenAI recruitment platforms. We help companies hire faster with an end-to-end product that covers job posting, sourcing, scoring and matching, and AI-driven assessments. We also run a candidate marketplace and a Recruitment as to Service team that fills roles for our customers. In this role you will sell both the platform and the services around it.

The Role

You’ll be an engineer who builds AI agents in production, sitting close to the customers who depend on them. This is a full-stack engineering job with an unusually short distance between your code and someone's actual workday. You’ll write Go and Python, design schemas, build evals, and present your solution to a senior executive at an enterprise - often in the same week.

What You’ll Do

• Design and ship production agents. You’ll build agents that are mission-critical from day one embedded in Teams, Slack, intranets, voice lines, and email, taking real actions against SAP, ServiceNow, Workday, and a long tail of systems nobody has heard of. These run at enterprise volume under enterprise scrutiny.
• Own the full lifecycle. Discovery, build, eval, launch, and the unglamorous months afterward where an agent goes from good to genuinely reliable.
• Work directly with the people whose problem it is. You’ll sit with leaders at global enterprises, extract the process from their heads, and decide what should be an agent, what should be a workflow, and what should stay human.

What You’ll Bring

• Experience building and scaling end-to-end production systems, with 5+ years of relevant engineering work
• Strong backend fundamentals - algorithms, data modeling, and comfort in more than one language, Python and Go especially
• Proven problem-solving in fast-changing, ambiguous environments where the requirements arrive in a meeting rather than a ticket
• A builder's mindset and high agency - you find a way to ship rather than waiting for the blocker to clear
• Comfort working directly with customers
• Clear, direct communication with technical and non-technical audiences alike

Even Better

• You've built or deployed LLM systems in production, and have opinions about evals
• Familiarity with agent tooling, RAG pipelines, MCP, and prompt engineering as an engineering discipline rather than a trick
• You've been a founder or founding engineer, and know how to balance craft against speed
• Experience integrating enterprise applications - HRIS, ITSM, ERP, ticketing - and the authentication that guards them
• You've worked with distributed, global teams and multi-tenant SaaS environments