Agent Engineer

Uplers Solutions Private Limited.; India; Remote; INR 1,500,000 - 2,600,000; Full time

Job summary

Uplers Solutions Private Limited is seeking an experienced Engineer to own a client voice or chat agent in production. You will work on end-to-end delivery, from requirements to pilot, production, and continuous improvement, ensuring compliance and alignment with client needs.

You have 2–5 years in production systems, strong Python, FastAPI, Kubernetes, and CI/CD. You'll collaborate with US enterprise clients, shaping agent behavior, tests, and deployment processes to drive business metrics.

Qualifications

• 2–5 years building and running production systems.
• Proficient in Python with async programming and relational DBs.
• Experience with Kubernetes and CI/CD pipelines.
• Comfortable with client interactions and documentation.

Responsibilities

• Own a client delivery end to end from requirements to pilot, production and iteration.
• Engineer the agent's behavior and write versioned instructions.
• Build and maintain automated evaluation tests for agent compliance.
• Debug live conversations by tracing system state and instructions.
• Collaborate with US enterprise clients to drive business metrics.

Skills

Python

FastAPI

Kubernetes

Async programming

Relational databases

Client communication

Tools

ArgoCD

OpenFGA

Ory

Twilio

Signoz

Job description

Experience: 2.00 + years

Salary: Confidential (based on experience)

Expected Notice Period: 15 Days

Shift: (GMT+05:30) Asia/Kolkata (IST)

Opportunity Type: Remote

Placement Type: Full Time Permanent position(Payroll and Compliance to be managed by: AI Agents Automating Business Workflows)

(*Note: This is a requirement for one of Uplers' client - AI Agents Automating Business Workflows)

What do you need for this opportunity?

Must have skills required:

AI Agents, and startup experience., ArgoCD, Chatbots, CI/CD, conversational AI, DeepEval, OpenFGA, Ory, Production LLM applications, Prompt Engineering, rag, Regulated industry experience, Signoz, STT/TTS, Temporal, Twilio, Voicebots, and technical documentation., Asynchronous programming, Automated Testing, backend development (FastAPI preferred), Debugging, relational databases (PostgreSQL preferred), Strong Python, Kubernetes, Websockets

AI Agents Automating Business Workflows is Looking for:

What you''''ll do

An Agent Engineer owns a client's voice or chat agent in production. Not a component of it, the whole thing: the procedure it follows, the instructions that govern how it speaks, the code that connects it to the client's systems, and the tests that prove it does what the documentation says. When a client says \"the bot offered a payment plan below our minimum,\" you're the person who works out why, fixes it, and explains the fix to the client. You'll ship changes that speak to real callers in your first two weeks.

• Own a client delivery end to end. Take requirements from first conversation through pilot, production, and continuous iteration as procedures change, volumes grow, and models improve.
• Engineer the agent's behavior. Write and maintain the instruction sets that determine what the agent says and when. Instructions are versioned, tested, and reviewed like code, because a wrong word in a disclosure is a compliance incident, not a UX bug.
• Build the evaluation gate. Automated tests that replay past conversations and check the agent follows the procedure. Nothing ships without passing them.
• Debug live conversations. Look up what the system knew at each moment, read the exact instructions the model was given, and work out why it responded the way it did.
• Work directly with clients. Sit in on calls with US enterprise clients, own the technical conversation, and watch your changes move their business metrics. Not many engineering roles put you this close to the people using what you build.

Example projects

Recent work by engineers on this team, all on live debt collection agents:

• Build an intent identification layer for a voice agent, so every response is grounded in what the caller actually asked rather than what the model assumes, sharply reducing hallucinations on live calls
• Extend the negotiation flow so the agent offers payment plans only within the limits the client has set, with guardrails that make out-of-bounds offers impossible rather than just unlikely
• Grow the eval suite that replays real collection calls and verifies every legally required disclosure was delivered, word for word, before any release ships

What we work with

Python with FastAPI, PostgreSQL, Temporal for background workflows, WebSockets holding real-time conversations open, and STT and TTS providers on the speech side, with LLMs via OpenAI and similar underneath. Everything runs on Kubernetes with ArgoCD-driven GitOps deployments, SigNoz for observability, DeepEval driving the eval suite our CI runs before anything reaches production, Ory and OpenFGA for identity and access management, and a lot of beautifully built internal agent architecture underneath.

What you''''ll bring

• 2 to 5 years building and running production systems. You've been on call for something you built and debugged it under pressure.
• You write Python another person can read, review others work thoughtfully, and debug by forming a theory and testing it, not by changing things until they work. Reading code you didn't write and working out what it does is the single most important skill in the role.
• You've worked with async code and a relational database.
• You’re comfortable in front of a client: take vague feedback, ask the right questions, leave with a scoped change.
• Strong written communication. Agent instructions, client explanations, and incident writeups are all writing, and an agent is only as precise as the instructions behind it.

Even better

• LLM systems in production: eval frameworks, agent tooling, RAG pipelines, structured prompting
• Conversational AI experience, voice or chat: dialogue design, IVR systems, chatbots, speech interfaces
• A regulated industry: finance, healthcare, insurance, collections
• Real-time or telephony systems: WebSockets, streaming audio, Twilio or similar
• Founder or founding engineer experience

Explicitly not required: prior \"AI engineering\" as a job title, or a computer science degree. Careful engineers who own outcomes pick this up fast.

How we work

Small teams per client, with real ownership. You'll have peers to pair with and review your work, and you'll review theirs. We review all code, we write things down, and we'd rather hear an honest \"I don't know yet\" than a confident wrong answer.

Our values

• Trust: We do the right thing, especially when nobody is checking. Clients hand us regulated conversations with their own customers, and we earn that every day.
• Transparency: We write things down, share the real numbers, and say \"I don't know yet\" out loud, with each other and with clients.
• Technically best solution: We choose what's right, not what's easiest or trendiest. When we notice we got it wrong, we fix it.
• Decisiveness: We decide quickly with the information we have, commit, and correct course fast when reality disagrees.
• Simplicity: We keep systems, processes, and words simple. Complexity is a cost we pay only when it clearly buys something.