Python Backend Architect/Engineer

Job Title

Python Full Stack Developer – AI

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.

The role involves building end-to-end web applications, integrating AI models, and collaborating with cross-functional teams to deliver innovative AI-driven solutions.

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.

· Develop CI/CD pipelines and manage deployments using Docker and Kubernetes.

· Write clean, reusable, and well-documented code following best practices.

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

Required Technical Skills

Backend

· Python

· Django

· Flask

· FastAPI

Frontend

· React.js / Angular / Vue.js

· HTML5

· CSS3

· JavaScript (ES6+)

· TypeScript

AI / Generative AI

· OpenAI API

· Azure OpenAI

· Gemini API

· Claude API

· Llama Models

· LangChain

Databases

· PostgreSQL

· MySQL

· MongoDB

· Redis

Cloud & DevOps

· AWS / Azure / Google Cloud Platform

· Docker

· Kubernetes

· Git

· GitHub

· Jenkins

· CI/CD

API Development

· REST APIs

· GraphQL (Preferred)

· API Integration

Preferred Skills

· Machine Learning fundamentals

· NLP (Natural Language Processing)

· Hugging Face Transformers

· TensorFlow or PyTorch

· Kafka or RabbitMQ

· Elasticsearch

· Microservices Architecture

· Authentication (OAuth2, JWT)

Qualifications

· Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.

· 6–9 years of experience in Python Full Stack Development.

· Hands-on experience with Generative AI and LLM-based application development.

· Experience working in Agile/Scrum environments. 

2–4 years of experience in backend development with Python or Golang.

● Solid understanding of RESTful APIs, microservices, and distributed systems.

● Strong knowledge of data structures, algorithms, and OOPS principles.

● Hands-on experience with relational and/or NoSQL databases.

● Familiarity with Linux development, Docker, and basic cloud concepts

(AWS/GCP/Azure).

● Proficiency with Git and version control workflows.

● Familiarity with AI-powered development tools or exposure to projects involving large

language models (LLMs) is a plus.

Strong analytical and debugging skills with the ability to solve complex problems.

Key Responsibilities

• Design, develop, and maintain scalable Python backend applications for enterprise use cases.
• Develop robust REST APIs and microservices using Python frameworks such as FastAPI, Flask, or Django.
• Design and implement scalable backend services with proper API integration, authentication, error handling, logging, and monitoring.
• Develop responsive and scalable React.js frontend applications.
• Implement React Hooks, state management, API integration, reusable components, and frontend development.
• Integrate React.js applications with Python backend APIs and microservices.
• Design and develop Generative AI and LLM-powered applications.
• Build and integrate Agentic AI / AI Agent solutions for enterprise use cases.
• Develop RAG (Retrieval-Augmented Generation) pipelines using enterprise data and knowledge sources.
• Work with embeddings, vector databases, and vector search for semantic retrieval and knowledge-based applications.
• Develop AI agent workflows using frameworks such as LangChain, LangGraph, Google ADK, or Semantic Kernel.
• Implement tool calling and function calling to enable AI agents to interact with APIs, databases, enterprise systems, and external services.
• Apply prompt engineering techniques to improve LLM response quality, accuracy, consistency, and reliability.
• Integrate LLMs and GenAI capabilities into full-stack applications.
• Develop multi-step AI workflows, agent orchestration, and intelligent automation solutions.
• Design APIs and services for seamless integration between AI components, backend services, databases, and frontend applications.
• Work with cloud platforms such as AWS, Azure, or GCP for application and AI solution deployment.
• Develop production-ready applications with focus on scalability, performance, security, reliability, and maintainability.
• Troubleshoot and optimize backend, frontend, API, RAG, LLM, and Agentic AI components.
• Collaborate with architects, software engineers, AI/ML engineers, product teams, and business stakeholders.
• Participate in code reviews, technical discussions, testing, deployment, and production support.

Mandatory Skills

• Python Backend Development
• REST API / Microservices
• FastAPI / Flask / Django
• React.js
• React Hooks / State Management
• Frontend Development & API Integration
• GenAI / LLM
• Agentic AI
• RAG
• Embeddings / Vector Search
• LangChain / LangGraph / Google ADK / Semantic Kernel
• Prompt Engineering
• Tool Calling / Function Calling
• Cloud – AWS / Azure / GCP

Preferred Candidate Profile

• 8.5+ years of overall software development experience.
• Strong hands-on experience in Python backend development and API/microservices development.
• Strong experience in React.js and full-stack application development.
• Practical experience building GenAI/LLM applications.
• Hands-on experience with Agentic AI and AI agent frameworks.
• Good understanding of RAG, embeddings, vector search, and LLM-based application architecture.
• Experience with LangChain, LangGraph, Google ADK, Semantic Kernel, or equivalent agent frameworks.
• Strong understanding of prompt engineering and tool/function calling.
• Experience integrating AI capabilities with APIs, databases, enterprise applications, and external systems.
• Hands-on experience with at least one major cloud platform such as AWS, Azure, or GCP.
• Strong problem-solving, debugging, communication, and collaboration skills.
• Candidates should be available for immediate / short-term joining.

Full-Stack Engineer (Backend Heavy)

Experience: 4–6 Years | Function: Engineering — Product | Location: On-site

About Us

We’re building the next generation of AI-powered business software, and we’re looking for people who want to shape that future with us. With Lumen, we’re reimagining how users interact with CRM — moving beyond screens, menus and dashboards to an intelligent interface where users can simply ask AI to take actions, retrieve knowledge, generate insights and get work done. With Agent Studio, we’re enabling businesses to build, test and deploy their own AI agents for real-world workflows. And with Invorto, we’re bringing AI to voice, allowing businesses to create intelligent voice agents tailored to their customer and operational use cases.

What makes this especially exciting is the stage and scale of the opportunity. You’ll get to work on genuinely hard problems across LLMs, agents, reasoning, orchestration, voice AI, evaluation, reliability and enterprise security — not as isolated experiments, but as products used in real business workflows. You’ll have the opportunity to build zero-to-one, own meaningful parts of the product end-to-end, work closely with customers, experiment rapidly, and see your work reach production at scale.

Why join now? Because the playbook for enterprise AI is still being written. You won’t just be implementing someone else’s roadmap — you’ll help define the product, architecture and experiences that become that playbook. Expect high ownership, fast iteration, hard technical and product problems, direct customer impact, and the chance to build AI systems that have to work reliably in the real world — not just in a demo.

About the Role

We are looking for a Full-Stack Engineer with a strong backend bias to help build end-to-end product experiences across Lumen and Agent Studio. You will own features from database and API design through to the front-end experience, working closely with product and design to ship AI-powered experiences that real business users depend on every day.

What You’ll Do

Design and build backend services and APIs in Python that power core product and AI-agent features.

Build front-end interfaces and experiences that let users interact naturally with AI agents, insights and CRM workflows.

Own features end-to-end — from data modeling and backend logic to UI implementation, testing and release.

Work with product managers and designers to translate requirements into well-architected, scalable systems.

Integrate with LLM-based and agentic backend systems built by the AI/ML engineering team.

Optimize application performance, reliability and code quality across the stack.

Engage directly with customers and customer success teams to understand workflows, triage issues and inform roadmap decisions.

What We’re Looking For

4–6 years of professional full-stack engineering experience, with a clear backend-heavy skill set in Python.

Strong experience designing and building REST/GraphQL APIs, data models and scalable backend services.

Working proficiency with modern front-end frameworks (e.g., React) to build and integrate user-facing features.

Experience with relational/NoSQL databases, caching and cloud infrastructure.

Ability to move fast in a zero-to-one environment while maintaining code quality and system reliability.

Strong communication skills — this is a customer-facing role, and you will be expected to clearly articulate technical concepts, decisions and trade-offs to both technical and non-technical stakeholders, including customers.

Good to Have

Experience building features on top of LLM or AI-agent backends.

Prior experience in CRM, SaaS or enterprise business applications.

Exposure to real-time or voice-based product interfaces.

Sr Backend Developer (Full Stack – Python / Django)

Preference: Please apply only if you are an IIT/NIT graduate and have strong hands-on experience in full-stack development with Python & Django.

Insurance/InsurTech experience is preferred. Strong engineering fundamentals and a willingness to learn the domain are more important.

Office location – Bangalore

Work mode – Onsite

Working Days – 5 days a week

Budget - 12-15 LPA

Work Experience - 2-5 years

Role Summary

We’re hiring Sr Backend Developers with strong full-stack Django expertise to own backend workstreams end-to-end and contribute to frontend development when needed. Hands-on Python/Django experience is essential.

(HTML, JavaScript, jQuery, CSS).

Key Responsibilities

 Design, build, and maintain scalable backend services and APIs for Fuse-OS

 Own medium-to-complex workstreams end-to-end: data models, APIs, background jobs, and light UI

wiring

 Improve reliability, performance, observability, and maintainability of production systems

 Apply sound engineering practices for multi-tenant SaaS (security, permissions, data isolation)

 Collaborate closely with frontend, QA, and product/delivery to ship high-quality releases

 Mentor other backend engineers through design discussions, pairing, and code reviews

 Participate in architecture discussions and help evolve platform technical standards

 Support production troubleshooting and continuous improvement of engineering quality

Required Skills & Qualifications

 Solid experience with Django REST Framework, asynchronous job processing (e.g., Celery), Redis, and

PostgreSQL

 Proven ability to design data models, write migrations, and ship maintainable APIs

 Full-stack capability: HTML, JavaScript, jQuery, and CSS sufficient to complete UI wiring without blocking

frontend

 Strong debugging skills across application, database, and background-job layers

 Experience collaborating in Agile teams with clear quality standards and delivery cadence

Preferred / Nice to Have

 Hands-on Selenium automation experience with Python (big plus)

 AWS familiarity (compute, storage, messaging, monitoring, IAM basics) — optional but strongly preferred

 Experience with multi-tenant architectures, containers, and production SaaS operations

 Exposure to document/data processing pipelines, reconciliation-style systems, or enterprise integrations

 Awareness of application security, RBAC, auditability, and privacy-by-design practices

 Interest in AI-assisted product workflows and intelligent automation

What We Offer

 Opportunity to build a category-defining Insurance Distribution Operating System (Fuse-OS)

 Work on modern multi-tenant SaaS architecture with meaningful ownership and mentoring

 Collaborative product and engineering culture focused on quality and customer outcomes

 Exposure to enterprise SaaS, AI-enabled workflows, and large-scale operational systems

Most sales tools help you send emails. We’re building something different.

At Salesforge, we’re creating autonomous AI agents that can:

Find the right prospects

Generate highly personalized outreach

Run conversations

And book meetings

All without human involvement.

Why this is interesting

A lot of AI products stop at “generate text.” We’re focused on outcomes.

That means solving problems like:

How do you generate messages that actually get replies?

How do you evaluate and improve agent performance over time?

How do you orchestrate millions of AI-driven interactions reliably?

How do you combine structured data + LLMs in a way that scales?

If you enjoy working at the intersection of systems + AI + real-world feedback loops, this will feel like a playground.

What you’ll be working on

You won’t be maintaining legacy systems.

You’ll be:

Designing and building core backend systems that power our AI agents

Creating APIs and services that handle high-scale, real-time workflows

Working with queues (Kafka / SQS / RabbitMQ) to orchestrate async systems

Thinking deeply about performance, cost, and reliability in AI pipelines

Shipping features end-to-end with a small, senior team

The team

We’re a small group of experienced builders. We move quickly, care about quality, and avoid unnecessary process.

No layers of management.

No long planning cycles.

Lots of ownership and autonomy.

What we’re looking for

5+ years of backend engineering experience

Strong system design fundamentals

Experience with distributed systems and async processing

Familiarity with relational and/or document databases

Clear communicator, low ego, high ownership

Why join

You’ll work on a product where the output is measurable (meetings booked, revenue generated)

You’ll have real ownership from day one

You’ll be early in building a new category (AI sales agents)

You’ll grow as fast as we do

Role Overview

We are looking for a skilled Python Full Stack / Agentic AI Engineer to design, develop, and deploy AI-powered applications and intelligent agentic workflows. The ideal candidate should have strong expertise in Python, FastAPI, LLMs, RAG, LangChain/LangGraph, and modern full-stack development.

You will work on building scalable backend services, integrating Large Language Models, developing AI agents, implementing Retrieval-Augmented Generation (RAG) pipelines, and creating production-ready AI applications.

Key Responsibilities

• Design and develop scalable backend applications using Python and FastAPI.
• Build and deploy Agentic AI solutions using LLMs and agent frameworks.
• Develop multi-step and multi-agent workflows using LangChain and LangGraph.
• Design and implement RAG (Retrieval-Augmented Generation) pipelines.
• Integrate LLMs such as OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source models.
• Develop prompt engineering strategies and structured LLM workflows.
• Work with vector databases and embedding models for semantic search and knowledge retrieval.
• Build APIs and microservices for AI-powered applications.
• Integrate AI services with databases, third-party APIs, and enterprise systems.
• Develop conversation memory, tool calling, function calling, and agent orchestration capabilities.
• Implement evaluation, monitoring, logging, guardrails, and error handling for AI applications.
• Optimize applications for performance, scalability, reliability, and cost.
• Collaborate with product managers, frontend developers, data engineers, and other stakeholders.
• Write clean, maintainable, well-tested, and production-ready code.
• Participate in architecture discussions, code reviews, testing, and deployment activities.

Required Skills

Programming & Backend

• Strong proficiency in Python.
• Hands-on experience with FastAPI, REST APIs, and backend development.
• Strong understanding of asynchronous programming, API design, authentication, and middleware.
• Experience with SQL/NoSQL databases.

Generative AI / Agentic AI

• Strong understanding of LLMs and Generative AI.
• Hands-on experience building AI Agents / Agentic AI applications.
• Experience with LangChain and/or LangGraph.
• Knowledge of agent orchestration, tool calling, function calling, memory, and workflow management.
• Strong understanding of prompt engineering.

RAG

• Experience designing and implementing RAG architectures.
• Knowledge of document ingestion, chunking, embeddings, vector search, retrieval, reranking, and response generation.
• Experience with vector databases such as FAISS, Chroma, Pinecone, Weaviate, Qdrant, or similar.

LLM & AI Integration

• Experience integrating commercial or open-source LLMs.
• Understanding of embeddings, context windows, temperature, token usage, and model selection.
• Experience with structured outputs and LLM-based workflows.
• Familiarity with LLM evaluation and observability is a plus.

Full Stack

• Working knowledge of HTML, CSS, JavaScript/TypeScript.
• Experience with React.js or similar frontend frameworks is preferred.
• Ability to integrate frontend applications with Python/FastAPI services.

Job Overview

Architect and build scalable, high-performance backend systems while working on mission-critical platforms that process real-time market data and portfolio analytics. The role also involves leveraging Generative AI capabilities to enhance data intelligence, automation, and user-facing features, while ensuring regulatory compliance and secure financial transactions.

Key Responsibilities

• Design, develop, and maintain scalable backend services and APIs using NodeJS and Python
• Build event-driven architectures using RabbitMQ and Kafka for real-time data processing
• Develop and manage data pipelines integrating PostgreSQL and BigQuery for analytics and warehousing
• Integrate and deploy Generative AI models (LLMs, embeddings, AI APIs) into backend systems for automation, insights, and intelligent workflows
• Design AI-powered features such as recommendation systems, document processing, or conversational interfaces
• Ensure system reliability, security, and low-latency performance for mission-critical systems
• Lead technical design discussions, conduct code reviews, and mentor junior engineers
• Optimize database queries, implement caching strategies, and improve overall system performance
• Collaborate with cross-functional teams to deliver end-to-end product features
• Implement monitoring, logging, and observability solutions

Required Skills and Qualifications

• 2+ years of professional backend development experience
• Strong expertise in NodeJS and Python for production-grade applications
• Proven experience building RESTful APIs and microservices architectures
• Experience working with Generative AI frameworks/APIs (OpenAI, LangChain, vector databases, prompt engineering)
• Understanding of integrating LLMs into production systems (RAG, embeddings, fine-tuning basics)
• Strong proficiency in PostgreSQL, including query optimization and schema design
• Hands-on experience with RabbitMQ and Kafka
• Experience with BigQuery or similar data warehousing solutions
• Solid understanding of distributed systems, scalability patterns, and high-traffic applications
• Strong knowledge of authentication, authorization, and security best practices
• Experience with Git, CI/CD pipelines, and modern development workflows
• Excellent problem-solving and debugging skills
• Exposure to fintech or financial services, cloud platforms (GCP/AWS/Azure), Docker/Kubernetes, caching tools (Redis/Memcached), and regulatory requirements (KYC, compliance, data privacy) is a plus

Apply directly at: https://wohlig.keka.com/careers/jobdetails/136351

Location: Hyderabad, India. Based at the KnackLabs headquarters, with occasional travel to client locations for workshops and reviews. This role does not involve extended onsite deployments.

About the Role

You will work as an AI Architect who designs the systems behind our client engagements: AI agents, RAG systems, automation platforms, and the conventional backend systems around them.

This is a hands-on design role, not a slideware role. You will scope architectures with clients, make the hard technical decisions, defend them in review, and stay accountable for how the systems perform in production.

You will work directly with clients. Everyone at KnackLabs does. You will sit in design discussions with client engineering teams, present architecture decisions to technical and business stakeholders, and answer for the choices you make.

A full KnackLabs engineering team in Hyderabad builds with you. You own the technical design and the quality of what ships.

What you'll own

1. Architecture - Design AI agents, RAG systems, integrations, and the scalable backend systems around them, for multiple client engagements.
2. Technical scoping - Work directly with clients to turn a business problem into a system design, with clear trade-offs and clear reasons.
3. Scale and reliability - Make sure what we build handles real load: data stores, queues, caching, horizontal scaling, and fault tolerance.
4. Design reviews - Review designs and builds across engagements. Set the technical bar and hold it.
5. Evaluation strategy - Define how we measure accuracy, safety, latency, and cost for the AI systems we ship.
6. Guiding engineers - Raise the level of the engineers building with you, through reviews and direct pairing.
7. Feedback to the platform - Feed what you learn across engagements back into our platform and internal tools.

What we are looking for

1. Around 7 or more years of software engineering experience, including direct work with customers on design or delivery.
2. Full-stack development experience with strength in backend technologies.
3. Experience designing and building scalable applications. You understand how large-scale distributed systems work: data partitioning, queues, caching, horizontal scaling, and fault tolerance.
4. At least 2 years of strong, hands-on AI experience with large language models in production.
5. You build with AI coding tools like Claude Code or Codex as your default way of working. You understand Claude Skills, have written skills yourself, use them actively, and have contributed to them.
6. Hands-on experience building retrieval-augmented generation (RAG) systems: chunking, embeddings, vector databases, retrieval, and reranking.
7. Hands-on experience building AI agents.
8. Strong programming skills in Python. Working knowledge of TypeScript or JavaScript.
9. Experience with at least one cloud platform (AWS, Azure, or GCP).
10. Clear communication. You can explain an architecture decision to an engineer and to a business leader, and defend it under questioning.
11. High ownership and comfort with ambiguity. You can take an unclear problem and turn it into a design.

Nice to have

1. Experience building evaluations to measure accuracy, safety, latency, and cost.
2. Experience with observability and tracing tools such as LangSmith or Braintrust.
3. Experience with on-premises or private cloud (VPC) deployments.
4. Experience deploying AI systems in regulated industries such as insurance, banking, or the public sector.
5. Experience with data engineering and pipelines.
6. A history of side projects, open source contributions, or products you shipped end-to-end.
7. Experience working at a consulting or professional services firm in a client-facing delivery role.

Stack and tools

1. Languages: Python and TypeScript.
2. Models: Claude and other frontier or open-source models, chosen to fit the customer.
3. AI patterns: RAG, agents, prompt engineering, skills, and evaluations.
4. Vector and retrieval: vector databases and retrieval pipelines.
5. Cloud: AWS, Azure, or GCP, on public or private cloud.
6. Integration: REST APIs and enterprise system connectors.

About the Role

We’re building the next generation of AI-powered business software, and we’re looking for people who want to shape that future with us. With Lumen, we’re reimagining how users interact with CRM — moving beyond screens, menus and dashboards to an intelligent interface where users can simply ask AI to take actions, retrieve knowledge, generate insights and get work done. With Agent Studio, we’re enabling businesses to build, test and deploy their own AI agents for real-world workflows. And with Invorto, we’re bringing AI to voice, allowing businesses to create intelligent voice agents tailored to their customer and operational use cases.

What makes this especially exciting is the stage and scale of the opportunity. You’ll get to work on genuinely hard problems across LLMs, agents, reasoning, orchestration, voice AI, evaluation, reliability and enterprise security — not as isolated experiments, but as products used in real business workflows. You’ll have the opportunity to build zero-to-one, own meaningful parts of the product end-to-end, work closely with customers, experiment rapidly, and see your work reach production at scale.

Why join now? Because the playbook for enterprise AI is still being written. You won’t just be implementing someone else’s roadmap — you’ll help define the product, architecture and experiences that become that playbook. Expect high ownership, fast iteration, hard technical and product problems, direct customer impact, and the chance to build AI systems that have to work reliably in the real world — not just in a demo.

About the Role

We are looking for a Senior AI/ML Backend Engineer to help build the core intelligence layer powering Lumen and Agent Studio. You will design and ship production-grade backend systems that integrate LLMs into real agentic workflows — taking actions, retrieving knowledge and generating insights inside a live CRM product used by real businesses. This is a hands-on, build-focused role with direct ownership of systems that ship to production.

What You’ll Do

• Design, build and scale backend services in Python that power LLM-driven and agentic features within Lumen and Agent Studio.
• Build and productionize agentic AI systems — including planning, tool use, orchestration, memory and multi-step task execution.
• Integrate LLMs into core product workflows, focusing on reliability, latency, cost and correctness at production scale.
• Build robust APIs and services that connect AI agents with CRM data, business logic and third-party systems.
• Own evaluation, testing and monitoring for AI features to ensure they behave reliably in real-world, not just demo, conditions.
• Collaborate closely with product, design and other engineers to take features from zero to one and iterate rapidly based on real usage and customer feedback.
• Work directly with customers and customer-facing teams to understand real workflows, debug issues and translate feedback into product and engineering decisions.

What We’re Looking For

• 2–4 years of professional backend engineering experience, with strong hands-on Python skills.
• Design and build LLM-powered agentic systems using frameworks such as LangChain, LlamaIndex, AutoGen, or CrewAI to automate complex, multi-step workflows.
• Should be hands-on with traditional Machine learning frameworks like Pytorch, Scikit-learn
• Solid understanding of API design, backend architecture, databases and distributed systems fundamentals.
• Familiarity with LLM orchestration concepts — prompting, tool/function calling, RAG, agent frameworks, evaluation and guardrails.
• Comfort working in a fast-paced, ambiguous, zero-to-one environment where you’ll be defining as much as building.
• Strong communication skills — this is a customer-facing role, and you will be expected to clearly articulate technical concepts, decisions and trade-offs to both technical and non-technical stakeholders, including customers.

Good to Have

• Experience with enterprise security, reliability or observability practices for AI systems.
• Prior experience working on CRM, SaaS or other enterprise business software.
• Exposure to voice AI or real-time systems.