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Python Engineer - AI Agents Development
Python Engineer - AI Agents Development

Python Engineer - AI Agents Development at Vikgol · Remote only · 2 - 4 years · ₹8L - ₹17L / yr (ESOP available) · Profitable · Remote only · Posted 7 Apr 2026

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Python Engineer - AI Agents Development

Sweta Raha's profile picture
Posted by Sweta Raha
2 - 4 yrs
₹8L - ₹17L / yr (ESOP available)
Remote only
Skills
Linux/Unix
skill iconPython
Artificial Intelligence (AI)

Description :


Job Title : Python Engineer- AI Agents & Code Optimization


Experience : 2+ Years


Employment Type : Full-time


Location : Remote


About the Role :


We are looking for a hands-on Software Engineer to build and improve AI agents that work directly on our production code.


Your core responsibility will be to design and evolve a specialized AI agent that deeply understands our codebase and actively helps make it faster, cleaner, simpler, and cheaper to maintain.


This is not a research role. This is real work on real systems with real business impact.


How We Work :


- Business impact first : Cheaper, Faster, Better


- Simple beats complex always


- Small changes, shipped fast


- You own your work end-to-end


- First question is always : Do we even need this?


- Flat team, zero micromanagement


- Decisions can change adaptability matters


- No long PRDs : one clear goal ? discuss ? execute


- Ship, measure, improve, repeat


What You Will Do :


- Build and use AI agents to optimize, refactor, and remove code


- Feed logs, metrics, and performance data back into AI agents


- Profile applications and identify performance bottlenecks


- Optimize SQL queries and database usage


- Improve deployment pipelines and release processes


- Continuously improve internal AI tooling


- Work closely with infrastructure and production systems


Tech You Should Be Comfortable With :


You dont need to be an expert in everything, but you should be comfortable working with :


- Linux CLI (Required)


- Python


- PHP


- SQL (MySQL or MariaDB)


- Shell scripting


- Large Language Models (LLMs)


What Were Looking For :


- 2+ years of software engineering experience (or strong hands-on projects)


- Solid understanding of performance optimization


- Experience cleaning up legacy or messy codebases


- Practical profiling and debugging skills


- Comfortable working close to infrastructure and deployments


- Automation-first mindset


- Ability to explain technical decisions clearly and simply in English


Nice to Have :


- Experience building AI agents


- Exposure to large or long-running systems


- CI/CD or deployment automation experience


When You Join :


- Career Growth : You are expected to grow into a tech lead, entrepreneur, or highly skilled specialist


- Bleeding-Edge Tech : Hands-on experience with alpha/beta software, cutting-edge infrastructure, and top tier hardware


- Global Exposure : Work with a global team and directly with C-level leadership


- Real Impact : Your code directly solves real user problems and moves the company forward

Read more
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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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About Vikgol

Founded :
2016
Type :
Services
Size :
0-20
Stage :
Profitable

About

Vikgol | Crafting Superior Software with a Focus on Code Quality Excellence
Read more

Company social profiles

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icon

The recruiter has not been active on this job recently. You may apply but please expect a delayed response.

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Job Title

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Experience: 6-9 Years

Location: Bangalore (Hybrid)

Employment Type: Full-Time

Job Summary

We are seeking a highly skilled Python Full Stack Developer with AI expertise to design, develop, and deploy scalable AI-powered applications. The ideal candidate should have strong experience in Python, Full Stack Development, REST APIs, modern frontend frameworks, and Generative AI technologies, including LLMs, prompt engineering, and AI integrations.

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Key Responsibilities

· Design, develop, and maintain scalable full-stack applications using Python.

· Build responsive and interactive user interfaces using React.js, Angular, or Vue.js.

· Develop backend services and RESTful APIs using Django, Flask, or FastAPI.

· Integrate Generative AI models such as OpenAI GPT, Claude, Gemini, or Llama into business applications.

· Develop AI-powered chatbots, assistants, document processing, and workflow automation solutions.

· Implement prompt engineering techniques to optimize AI model performance.

· Build Retrieval-Augmented Generation (RAG) pipelines using vector databases.

· Work with LangChain, LangGraph, or LlamaIndex for LLM orchestration.

· Integrate AI APIs and third-party services into enterprise applications.

· Design and optimize SQL and NoSQL databases.

· Deploy applications on AWS, Azure, or GCP.

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· Participate in Agile ceremonies, code reviews, and sprint planning.

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Frontend

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· HTML5

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· JavaScript (ES6+)

· TypeScript

AI / Generative AI

· OpenAI API

· Azure OpenAI

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· Claude API

· Llama Models

· LangChain

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· MySQL

· MongoDB

· Redis

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· Docker

· Kubernetes

· Git

· GitHub

· Jenkins

· CI/CD

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· GraphQL (Preferred)

· API Integration

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· NLP (Natural Language Processing)

· Hugging Face Transformers

· TensorFlow or PyTorch

· Kafka or RabbitMQ

· Elasticsearch

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Model the per-request and per-user cost of every AI feature before it ships.

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Design, test, and iterate prompts with measured outcomes.

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Run benchmarks across models and prompt variants before locking in a design.


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AI Feature Shipped to Production (Mandatory)

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2 to 4 Years of Professional Software or AI Engineering Experience

With at least one production AI feature owned end to end.


Strong Python Proficiency and API Development with FastAPI

Comfort with type hints, async, packaging, testing, streaming responses, and authentication.

Production-grade Python, not notebook-only code.


Hands-on Depth Across the LLM and Agent Stack

Working experience with at least two of OpenAI, Anthropic Claude, Google Gemini, or self-hosted open-weight models (vLLM, Ollama, Together, Replicate).

Working familiarity with at least one agent framework (LangGraph, CrewAI, AutoGen, LlamaIndex Agents) or hand-rolled equivalent.

Working knowledge of RAG, embeddings, and vector databases (Pinecone, Weaviate, Qdrant, pgvector, Chroma).


Solutioning Speed and POC Velocity

Demonstrated ability to move from a fuzzy problem to a working prototype in days.

Strong instinct for what to build first, what to defer, and what to throw away.


Cost Discipline for Production AI

Ability to calculate, monitor, and optimise the cost of LLM APIs, tokens, embeddings, vector store usage, and infrastructure.

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Working knowledge of EC2, S3, IAM, and at least one of Bedrock, SageMaker, or equivalent.


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Strong Written and Spoken English Communication

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  • MCP server authoring
  • eval framework experience (LangSmith, Promptfoo, Ragas, DeepEval)
  • open-source AI contributions
  • multi-modal models (vision, audio)
Read more
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Concretely, the kind of work you'd have done here last week would include enhancing agent memory systems, runtime and scheduling reliability and predictability, adding new capability and tools to deployed agents, operator tools, live system debugging and benchmarking various models for price, latency and quality. And that is just last week. We are a small nimble startup rapidly working to address customer needs in this growing space, so things change rapidly.


What we're looking for

  • More than 7 years of software engineering, with real production ownership of distributed or stateful systems - you've been paged for something you built and made it not happen again.
  • Strong understanding of LLM based native app building, combining classic and model driven applications to get the best of both. You've built on LLMs beyond demos: agent frameworks, tool use, context management, eval fixtures, and you know why "it worked in the transcript" isn't evidence.
  • Python and shell in production settings; comfortable in TypeScript/Node. You write boring, testable code and prefer the standard library to a new dependency.
  • Systems taste: append-only logs, idempotent reconciliation, fold-the-events state machines, and read-only debugging surfaces feel like home.
  • Evidence discipline: tests before features, claims backed by quoted observations, decisions written down.


Nice to have

  • Experience running the combination of multi-tenant and single-tenant / on-prem-style fleets with ability to handle per-customer isolation, upgrade paths, migration compatibility in both setups.
  • Security instincts for products that touch highly sensitive data and systems, including things like executives' email, calendars, and messages: least privilege, loopback-only services, secrets that never hit a log.
  • You already orchestrate AI coding agents in your own workflow and have opinions about where they break.


How we work

Small team, high trust, written decisions. Designs get adversarial review before code; PRs get automated review driven to zero open findings; features aren't done until verified on a live system. AI agents do a large share of the implementation, your leverage is judgment: framing the problem, freezing the right design, and knowing when the machine is wrong.

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MS OUTSOURCING
Remote only
3 - 5 yrs
₹4L - ₹8L / yr
skill iconPython
skill iconDjango

We are looking for an experienced Software Engineer to join an AI engineering startup developing a document collection platform for accountants and professional services firms. 


Preference to candidates from Kerala, India.


The product eliminates the friction involved in gathering client files by automating document requests, centralising their collection, and organising incoming documents according to each organisation’s preferred folder structure.


The ideal candidate will be able to take ownership of work from start to finish, communicate clearly, and deliver high-quality solutions within tight timeframes.


What You’ll Work On


You’ll work with Python and Django daily, including models, views, templates, background jobs, and the wider product around them.


The frontend uses Django templates with HTMX and Alpine.js, built with Vite, TypeScript, and Tailwind CSS. The stack runs in Docker using PostgreSQL, Redis, RabbitMQ, and Celery.


You may also assist with ancillary projects, including custom integrations.


Project-based training will be provided.


Technology Stack


Backend: Python, Django, PostgreSQL, Celery, Redis and RabbitMQ

Frontend: Django Templates, HTMX, Alpine.js, Vite, TypeScript and Tailwind CSS

Infrastructure: Docker


Must Have

  • Strong Python and Django skills
  • Comfortable working with Docker
  • Fluent written and spoken English
  • Clear communication skills, including providing concise updates, asking honest questions, and writing information that others can act on
  • Evidence of exceptional ability—not simply a list of tools, but something challenging you have built or solved

Preference will be given to candidates with at least three years of relevant professional experience.


Nice to Have

  • Frontend experience with HTML, CSS and JavaScript
  • Experience with HTMX, Alpine.js, TypeScript or Tailwind CSS
  • Knowledge of PostgreSQL, Celery or pytest
  • Experience with integrations, including APIs, OAuth and cloud storage
  • Basic accounting knowledge

How to Apply

Please do not send a generic CV alone. Your application must include:

  1. Evidence of exceptional ability: Describe a project, open-source contribution, production system or challenging problem you solved. Include a link to the repository, write-up or demo where possible. Focus on your personal contribution by detailing the specific parts of the project where you played a critical role and explaining precisely what you built or solved.
  2. What you accomplished: Provide a short explanation of the outcome in your own words.
  3. The hardest part: Explain the hardest part of the problem and how you dealt with it.
  4. Your use of AI: Explain whether you use AI in your work and, if so, how you use it.
  5. Your professional experience and interests: Include a brief paragraph summarising your professional experience and general interests.

Applications that do not include the above Croissant details above will not be considered.


What We Offer

  • For the right candidate, salary will not be a constraint
  • Project-based training
  • A rewarding career with genuine opportunities for professional growth
  • The opportunity to work on an innovative AI-driven product
  • A remote, full-time position

Job Details and Application Submission


Location: Remote

Employment Type: Full-time

Contract: One-year contract, with the possibility of extension based on satisfactory performance

Probationary Period: Six months

Preferred Experience: Three or more years

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Zeuron.AI
at Zeuron.AI
1 candid answer
Kavitha Rajan
Posted by Kavitha Rajan
Bengaluru (Bangalore)
1 - 5 yrs
₹6L - ₹10L / yr
skill iconMachine Learning (ML)
Artificial Intelligence (AI)
Computer Vision
skill iconFlutter
Embedded C
+2 more

Job Title: Software/Hardware Engineer (IIT/NIT)

Location: Bangalore

Website: https://www.zeuron.ai

Experience: 1-5Years

CTC: 6-10 LPA

No Freshers


About the Company

Zeuron.ai is a Bangalore-based deep-tech startup founded in 2019, focused on building brain-inspired computing and AI-driven healthcare solutions. The company combines neuroscience, AI, and gaming to create innovative digital therapeutics and neurotechnology platforms for improving brain health, rehabilitation, and overall well-being.



The role

Zeuron.ai is looking for hands-on software engineers who can turn an incomplete brief into reliable, usable software. You will work as an individual contributor, make sound technical decisions and take responsibility for the quality of what you deliver.

AI coding tools will be part of the workflow. We expect you to understand the underlying software well enough to build and debug without an LLM, then use AI to accelerate implementation, exploration and verification. You remain accountable for the result.


What you will own

• End-to-end delivery: clarify requirements, break work into achievable steps, implement features, test them, deploy them and respond to issues after release.

• Product decisions: understand the user problem, question unclear requirements and explain trade-offs between speed, quality, complexity and maintainability.

• Reliable software: investigate defects, identify root causes and improve error handling, performance and usability.

• Engineering continuity: maintain readable code, useful documentation and clear handovers so that others can run, understand and extend your work.


Engineering expectations

We value demonstrated building ability, technical reasoning and sound judgement. Tool familiarity should be supported by evidence of software you have actually delivered.

Software fundamentals

• Programming: practical fluency in at least one programming language, with an understanding of data structures, control flow, modularity and common complexity trade-offs.

• Applications and services: understand how interfaces, APIs, business logic and data storage interact. Be able to trace a failure across these boundaries.

• Data: work with databases, reason about data models and queries, and handle validation, consistency and errors appropriately.

• Development workflow: use Git confidently, review changes, manage dependencies and keep development and deployment instructions reproducible.

• Testing and debugging: reproduce failures, form hypotheses, inspect logs and isolate causes. Test important behaviour and edge cases rather than relying on a successful demo.

• Security and reliability: recognise basic risks around authentication, access control, secrets, input handling and third-party dependencies.


Build independently. Use AI effectively.

• Without LLMs: write and modify code, diagnose defects, explain design choices and use documentation to solve unfamiliar problems independently.

• With AI coding tools: frame tasks clearly, supply relevant context, use generated suggestions selectively and inspect the resulting changes.

• Verify before accepting: check correctness, integration, security and maintainability. Recognise invented APIs, fragile assumptions and plausible-looking code that does not solve the actual problem.

• Protect information: use approved tools and handle credentials, proprietary code and user data responsibly.


Evidence we want to discuss

Be prepared to walk through a project you contributed to: the problem, your specific contribution, important technical decisions, a difficult bug and how you verified the result. Public repositories or demos are useful where available; do not share confidential material from previous employers.


Ownership, growth & applying

How you will work

• Act as an owner: follow through on agreed deliverables, raise blockers early and communicate progress with concrete evidence.

• Work with the team: collaborate with product and engineering colleagues, accept review constructively and explain technical choices clearly.

• Learn with purpose: pick up unfamiliar tools when the problem requires them, while keeping the solution proportionate to the need.

• Grow through contribution: begin with hands-on individual-contributor responsibility, with potential to take on broader product or team responsibility as delivery, judgement and collaboration develop.


What strong performance looks like

Working features that meet agreed requirements; clear reasoning about implementation; defects investigated systematically; code that others can maintain; and AI-assisted work whose quality you can explain and verify.


Eligibility and compensation

Experience: 1-5 years of hands-on software development experience only.

Freshers are not considered.

Locations: Bengaluru and Belagavi.

Annual CTC : 6-10 LPA

The offer will depend on experience, interview performance and growth potential.


What to expect in the assessment

Be prepared for a discussion of your previous work, a practical coding or debugging task without LLM assistance, and an assessment of how you use AI coding tools and verify their output. We will also discuss product judgement, ownership and collaboration.

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