Python Ai/ML Engineer

Job Title : Full-Stack AI Product Engineer

Experience : 3+ Years

Work Mode : Remote

Time Zone : IST

Engagement Type : Freelance

Availability : Must be comfortable attending US client calls during IST night hours.

Role Overview :

We are looking for a Full-Stack AI Product Engineer with hands-on experience building and deploying production-ready AI-powered applications. The ideal candidate should have strong Python backend development skills, practical expertise in LLMs, AI agents, RAG pipelines and tool calling, along with basic frontend development knowledge.

Mandatory Skills :

Python, FastAPI, AI / LLMs, AI Agents, RAG, Tool Calling, PostgreSQL, Redis, Docker, GCP / Cloud Run, CI/CD, Basic React.js / Next.js.

Key Responsibilities :

• Design, develop and maintain AI-powered products using Python and FastAPI.
• Build and integrate LLM-based applications, AI agents, RAG pipelines and tool-calling workflows.
• Develop scalable backend services and REST APIs.
• Work with PostgreSQL and Redis for data storage, caching and performance optimization.
• Containerize applications using Docker and deploy services on GCP, preferably Cloud Run.
• Implement CI/CD pipelines and follow production deployment best practices.
• Develop and integrate basic frontend features using React.js or Next.js.
• Troubleshoot production issues, optimize performance and ensure application reliability.
• Collaborate with US-based clients and stakeholders during IST night hours when required.

Required Skills :

• 3+ years of relevant software development experience.
• Strong proficiency in Python and FastAPI.
• Hands-on experience with AI / LLMs and production-level AI product development.
• Practical experience building AI agents, RAG pipelines and tool / function-calling workflows.
• Good knowledge of PostgreSQL and Redis.
• Experience with Docker, GCP / Cloud Run and CI/CD pipelines.
• Basic working knowledge of React.js or Next.js.
• Understanding of REST APIs, application architecture, deployment and production debugging.
• Excellent problem-solving and communication skills.

Preferred Qualifications :

• Experience deploying and maintaining AI applications in production.
• Familiarity with LLM orchestration frameworks and vector databases.
• Experience with cloud-native application development and monitoring.

Important Requirements :

• Must have demonstrable, hands-on experience delivering production-grade AI products.
• Must be comfortable working remotely and coordinating with US clients during IST night hours.

Responsibilities:

• Architect, develop, and maintain backend components for our Risk Decisioning Platform.
• Build and orchestrate scalable backend services that automate, optimize, and monitor high-value credit and risk decisions in real time.
• Integrate with ORM layers - such as SQLAlchemy - and multi-RDBMS solutions (Postgres, MySQL, Oracle, MSSQL, etc. ) to ensure data integrity, scalability, and compliance.
• Collaborate closely with Product Team, Data Scientists, QA Teams to create extensible APIs, workflow automation, and AI governance features.
• Architect workflows for privacy, auditability, versioned traceability, and role-based access control, ensuring adherence to regulatory frameworks.
• Take ownership from requirements to deployment, seeing your code deliver real impact in the lives of customers and end users.

Requirements:

• Proficiency in Python, SQLAlchemy (or similar ORM), and SQL databases.
• Experience developing and maintaining scalable backend services, including API, data orchestration, ML workflows, and workflow automation.
• Solid understanding of data modeling, distributed systems, and backend architecture for regulated environments.
• Curiosity and drive to work at the intersection of AI/ML, fintech, and regulatory technology.
• Experience mentoring and guiding junior developers.

Technical Skills:

• Languages: Python 3.9+, SQL, JavaScript/TypeScript, Angular.
• Frameworks: Flask, SQLAlchemy, Celery, Marshmallow, Apache Spark.
• Databases: PostgreSQL, Oracle, SQL Server, Redis.
• Tools: pytest, Docker, Git, Nx.
• Cloud: Experience with AWS, Azure, or GCP preferred.
• Monitoring: Familiarity with OpenTelemetry and logging frameworks.

Key Responsibilities

• Design, develop, and maintain scalable applications using Python.
• Build and integrate AI-powered solutions into existing applications.
• Develop REST APIs and backend services.
• Work with AI/ML models, LLMs, and Generative AI technologies where applicable.
• Integrate AI services and APIs into business applications.
• Write clean, maintainable, and efficient code.
• Collaborate with cross-functional teams to deliver high-quality solutions.
• Troubleshoot issues and optimize application performance.

Must-Have Skills

• Strong hands-on experience in Python development.
• Good understanding of Python frameworks such as FastAPI, Flask, or Django.
• Experience in REST API development and backend services.
• Knowledge or experience in AI/ML concepts.
• Understanding of application development, debugging, and problem-solving.
• Good understanding of databases and data handling.

Good-to-Have Skills

• Hands-on experience with Generative AI and Large Language Models (LLMs).
• Experience with AI APIs and frameworks such as LangChain or LlamaIndex.
• Knowledge of Retrieval-Augmented Generation (RAG), embeddings, and vector databases.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Experience with Docker, Kubernetes, or CI/CD pipelines.

Job Summary

We are looking for a skilled Python Developer with experience in Generative AI and Agentic AI to develop AI-powered applications and scalable backend services.

Mandatory Skills

• Python
• Generative AI (GenAI) / Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• LangChain / LangGraph
• Agentic AI
• FastAPI
• REST API development
• Vector Databases
• Prompt Engineering
• Microservices

Key Responsibilities

• Develop and maintain Python-based applications and backend services.
• Build GenAI/LLM-powered applications and AI solutions.
• Implement RAG pipelines for document processing and information retrieval.
• Develop AI agents using LangChain/LangGraph and Agentic AI frameworks.
• Build and integrate REST APIs using FastAPI.
• Work with vector databases for embeddings, semantic search, and retrieval.
• Design and optimize prompts to improve LLM response quality.
• Develop scalable microservices and integrate AI models into applications.
• Collaborate with cross-functional teams to deliver AI-based solutions.
• Troubleshoot, test, and optimize application performance.

Required Qualifications

• 4–6 years of experience in Python development.
• Hands-on experience with GenAI/LLMs, RAG, and Agentic AI.
• Practical experience with LangChain/LangGraph, FastAPI, and REST APIs.
• Knowledge of vector databases, prompt engineering, and microservices.
• Strong problem-solving and debugging skills.
• Ability to develop and deploy production-ready AI applications.

AI / Backend Engineer — Remote (India / Overseas)

Company: Ink'd

Compensation: $1,500–$2,500 USD/month, depending on experience

Type: Independent contractor, long-term opportunity

Ink'd is building a voice-first AI platform for residential real estate transactions. Our AI assistant allows real estate agents to generate contracts, automate workflows, and complete transaction documentation through natural conversation.

We're looking for a highly capable AI/backend engineer to help scale and maintain our production platform.

Responsibilities

• Build and maintain production AI agent workflows
• Develop integrations with third-party APIs and services
• Work with LLMs, structured data extraction, and document generation
• Troubleshoot production systems and improve reliability
• Build scalable backend services and maintain databases
• Collaborate directly with the founder and engineering team

Technical experience

• Python, FastAPI, Node.js, and REST APIs
• LLM APIs, tool calling, and agent orchestration
• PostgreSQL and cloud infrastructure
• GitHub, CI/CD, debugging, and deployment
• Experience with voice AI, WebSockets, or document processing is a major plus

What we're looking for

Someone who has independently shipped production software, can troubleshoot unfamiliar systems, communicates clearly, and takes ownership of their work.

Please include your GitHub, two examples of production systems you've built, your specific contributions, monthly compensation expectations, and availability.

Full Stack Developer – AI/ML & GenAI

Location: Mumbai

Experience: 7–9 Years

Employment Type: Full-time

Virtual Drive: Saturday

We are looking for a Python Full Stack Developer with 3+ years of hands-on experience in AI/ML and Generative AI.

Key Skills: Python Full Stack, FastAPI/Flask/Django, React/Angular, AI/ML, GenAI, LLMs, RAG, Embeddings, Vector Databases, Cloud (AWS/Azure/GCP), CI/CD, Docker & Kubernetes.

Job Description

We are looking for an experienced Python Full Stack – GenAI / Agentic AI Engineer with 7+ years of experience in software development and strong hands-on expertise in Python backend development, React JS, Generative AI, and Agentic AI.

The ideal candidate should have experience building scalable backend services, modern web applications, and AI-powered applications using LLMs, RAG, agentic frameworks, and cloud platforms.

Key Responsibilities

• Design, develop, and maintain scalable backend applications using Python.
• Develop robust REST APIs and microservices using FastAPI, Flask, or Django.
• Design API architecture, authentication mechanisms, error handling, and integrations.
• Develop responsive and interactive frontend applications using React JS.
• Work with React components, hooks, state management, and API integrations.
• Build and integrate Generative AI and Agentic AI applications using LLMs.
• Develop AI agents using frameworks such as LangChain and LangGraph.
• Implement RAG, embeddings, vector search, tool calling, memory, planning, and reasoning.
• Design and implement multi-agent systems and AI workflows.
• Apply prompt engineering techniques and appropriate guardrails for AI applications.
• Integrate AI applications with cloud-based AI platforms and services.
• Deploy applications using containers and cloud platforms.
• Work with CI/CD pipelines and application monitoring.
• Collaborate with cross-functional teams to design and deliver scalable solutions.

Required Skills

• 7+ years of overall software development experience.
• Strong hands-on experience in Python.
• Strong experience with FastAPI and REST API development.
• Experience with microservices architecture and API design.
• Hands-on experience with React JS.
• Strong experience in Generative AI / LLM applications.
• Hands-on experience in Agentic AI development.
• Experience with LangChain / LangGraph.
• Strong understanding of RAG, embeddings, vector search, and tool calling.
• Experience with multi-agent systems, memory, planning, and reasoning.
• Experience with at least one major cloud platform – AWS / Azure / GCP.
• Experience with containers, CI/CD, deployment, and monitoring.

Preferred Skills

• Google ADK
• Semantic Kernel
• Azure OpenAI
• Vertex AI
• AWS Bedrock
• Docker / Kubernetes
• AI application monitoring and observability
• Frontend testing and application performance optimization

Opportunity Details

Role: Python Full Stack – GenAI / Agentic AI Engineer

Experience: 7+ Years

Location: Hyderabad

Employment: Permanent Position

Work Mode: As per client requirement

Mandate Skills: Python, FastAPI, React JS, Agentic AI, LangChain/LangGraph, RAG, LLM, Cloud

Interview Focus Areas

Candidates should be prepared to demonstrate practical experience in:

• Python backend development
• FastAPI and REST APIs
• Microservices and API design
• React JS
• LLM / Generative AI applications
• Agentic AI architecture
• LangChain / LangGraph
• RAG and vector search
• Tool calling and multi-agent systems
• Cloud deployment and CI/CD

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.

Proficient

Python Backend Development

Python, REST APIs, Microservices, FastAPI, Flask, Django, API Design, Authentication, Error Handling

Design, implement, and maintain scalable backend systems using Python frameworks. Build robust REST APIs, ensure secure authentication, and handle errors gracefully. Demonstrate expertise in microservices architecture and API design.

35

Proficient

React JS

React JS, Components, Hooks, State Management, API Integration, Responsive UI, Frontend Testing

Develop responsive and interactive user interfaces using React JS. Effectively use components, hooks, and state management. Integrate APIs and ensure frontend code is well-tested and maintainable.

30

Proficient

Gen AI / Agentic AI

LLMs, Agentic AI, LangChain, LangGraph, Google ADK, Semantic Kernel, Prompt Engineering, Tool Calling, RAG, Embeddings, Vector Search, Memory, Planning, Reasoning, Multi-Agent Systems, Guardrails, Azure OpenAI, Vertex AI, AWS Bedrock

Demonstrate hands-on experience with LLMs and agentic AI frameworks. Build, integrate, and optimize AI agents using modern tools and platforms. Show proficiency in prompt engineering, tool calling, RAG, embeddings, and multi-agent systems.

30

Advanced

Cloud & Deployment

AWS, Azure, GCP, Cloud Deployment, Containers, CI/CD, Application Hosting, Monitoring

Deploy applications to cloud platforms, manage containers, set up CI/CD pipelines, and monitor application health. Demonstrate familiarity with at least one major cloud provider.