AI / Backend Engineer — Remote (India / Overseas) at Inkd · Remote only · 5 - 10 years · $18K - $35K / yr · Remote only · Posted 19 Oct 2026

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.

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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 strong Senior Python Engineer with hands-on AI/ML and Automation experience to join
our engineering team.
The engineer will work on high-scale backend systems, intelligent automation platforms, OCR/document
processing, AI-powered workflows, browser automation and integrations across multiple products.
This is not a role for someone whose AI experience is limited to calling LLM APIs. We need an engineer who
understands Python deeply and has built, deployed and maintained real production systems.
Experience Requirements
l Minimum 4 years of professional software development experience, primarily using Python.
l Minimum 2 years of practical hands-on experience in AI/ML, intelligent automation or closely related production
systems.
l Candidates with 4-6+ years of strong relevant experience are preferred.
l Strong production/backend engineering experience is essential.
Core Python & Backend Skills
l Python; FastAPI / Django / Flask; REST APIs and backend service development.
l Async programming and concurrency; multithreading / multiprocessing where appropriate.
l PostgreSQL / MySQL; Redis; background jobs and task queues such as Celery.
l WebSockets / real-time communication where required; authentication and authorization; API integrations.
l Docker; Linux; Git; logging, debugging and production troubleshooting.
l Ability to build fast, reliable and scalable Python services rather than only scripts.
AI / ML Requirements
l Machine Learning fundamentals; model training, evaluation and inference; data preprocessing and feature
engineering.
l Scikit-learn; PyTorch or TensorFlow; NLP.
l Embeddings, semantic search and vector databases.
l LLM integrations, prompt engineering, structured output and tool/function calling.
l RAG pipelines; AI agents / agentic workflows.
l OpenAI, Gemini, Claude or equivalent integrations; local/open-source model integration where appropriate.
l Understanding of model selection, accuracy, latency and cost trade-offs.
Automation Engineering
l Playwright; Puppeteer or equivalent browser automation frameworks; Selenium where appropriate.
l Headless browser and web workflow automation; form/repetitive task automation.
l Session/cookie management; file upload/download automation; API + browser hybrid automation.
l Retry and recovery mechanisms; scheduling and background execution.
l Queue-based automation workers; parallel/concurrent task processing.
About the Company
The client is revolutionising the way businesses operate through cutting-edge technological solutions. Their focus is on developing intelligent agents and agentic workflows that automate processes and eliminate the need for human effort wherever possible. By leveraging
advanced AI and machine learning, they create systems that enhance productivity and drive efficiency.
Their expertise extends to the fintech, healthcare and medical technology sectors, where they develop innovative solutions that improve patient outcomes and streamline medical operations.
From medical devices to healthcare platforms, their work sits at the intersection of technology and medicine, pushing the boundaries of what's possible. The team is dedicated to continuous learning and growth, ensuring the team members are always at the forefront of the tech landscape.
About the Role
This is a senior, hands-on engineering role at the heart of our product team. You will be one of the most technical people in the room — setting the architecture for our real-time voice AI
agents and building the hardest parts of it yourself. From the systems that power live conversations to the interfaces our clients rely on, you will own how the product is engineered end to end.
We are looking for a genuine lead full-stack engineer with the depth to make architecture decisions that hold up as we scale, and the appetite to still be in the code every day. You should be as comfortable designing the backend services behind a live voice agent as you are shaping a clean interface on top of them — and comfortable being the person others turn to when something is hard.
You will work directly with the founder and product leadership on a fast-moving product, with real influence over technical direction. This is a role for someone who wants ownership at the level of "how the whole thing is built," not just individual features — and who raises the bar for
everyone around them.
What You'll Own
Set the technical direction
- Own the architecture of our core systems — the real-time voice agents, backend
- services, data and APIs — making the decisions that keep the product fast, reliable and scalable as it grows.
- Lead the hardest engineering problems and solve them personally.
- Establish engineering standards — code quality, review practices, testing and technical patterns that the team builds to.
- Drive technical strategy with the founder and product leadership — shaping the roadmap, flagging risk early, and turning product ambition into a sound technical plan.
Build the product end to end
- Design, build and ship features across the stack — backend services, APIs and front-ends — owning them from idea to production.
- Build the client-facing surfaces — dashboards, review tools and configuration interfaces that let our clients run and trust the product.
- Design and evolve the data models and APIs that hold up as we scale across clients.
Make it reliable and fast
- Own production quality — put the monitoring and alerting in place so issues are caught before clients feel them, and performance stays within target.
- Care about performance — find and fix bottlenecks across the stack.
- Build for correctness — put the testing and evaluation in place that keeps the product behaving predictably as it changes.
Lead through the team
- Mentor and grow engineers — through code review, pairing, and setting a technical example others learn from.
- Multiply the team's output — unblock others and lift the overall quality of the codebase.
- Take features from ambiguity to done — turn a rough product goal into a shipped, working capability with minimal hand-holding, and help others do the same.
What We're Looking For
- 8+ years of professional software engineering experience, with significant depth across backend and a track record of owning systems, not just features.
- Strong backend engineering, ideally in Python — building and scaling production services and APIs..
- Proven architecture and system-design ability — you have designed systems that scaled, and can reason clearly about trade-offs.
- Solid fundamentals across APIs, databases and cloud infrastructure.
- Experience building real-time and/or AI-powered products — or clear, demonstrable ability to lead in this area.
- A history of technical leadership — setting standards, mentoring engineers, and being trusted with the hardest problems — while remaining hands-on.
- Excellent communication and a genuine ownership mindset — someone who can be handed an ambiguous, high-stakes problem and be trusted to see it through.
Nice to Have
- Experience working with AI / large language models in production.
- Experience with voice or other real-time products.
- Exposure to healthcare, fintech, or other regulated / high-stakes domains.
- Experience as an early or senior engineer in a startup, where you set direction and wore many hats.
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.
Proficient
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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.
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AWS, Azure, GCP, Cloud Deployment, Containers, CI/CD, Application Hosting, Monitoring
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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.
ou will work closely with AI engineers, product teams, and domain experts to build intelligent document processing and knowledge automation solutions. Responsibilities include:
- Develop AI-powered document ingestion and processing pipelines.
- Build knowledge extraction engines using NLP, Machine Learning, and Generative AI.
- Develop document-to-knowledge compilers that transform PDFs, Word documents, policies, regulations, and manuals into structured knowledge.
- Build AI agents and Agentic AI workflows for enterprise automation.
- Develop rule extraction and rule generation frameworks from business documents.
- Create semantic search and enterprise knowledge retrieval solutions.
- Develop backend APIs and AI services using Python.
- Design and optimize document processing pipelines for scalability and performance.
- Build and maintain MySQL databases for knowledge repositories and AI applications.
- Integrate LLMs from providers such as OpenAI, Azure OpenAI, Gemini, Claude, and open-source ecosystems.
- Collaborate with cross-functional teams to design scalable AI architectures.
- Participate in code reviews and follow software engineering best practices.
- Continuously evaluate and adopt emerging AI and GenAI technologies.
REQUIRED SKILLS — PROGRAMMING & DEVELOPMENT
- Strong proficiency in Python and a solid understanding of Object-Oriented Programming (OOP).
- Experience building REST APIs and backend services.
- Experience working with JSON, XML, and structured data formats.
- Knowledge of software design patterns and scalable architecture.
- Strong debugging, analytical, and problem-solving skills.
ARTIFICIAL INTELLIGENCE & MACHINE LEARNING
- Strong understanding of Machine Learning concepts and algorithms.
- Experience with Natural Language Processing (NLP) and Generative AI solutions.
- Hands-on experience with Large Language Models (LLMs).
- Understanding of prompt engineering techniques.
- Knowledge of Agentic AI concepts and AI agent architectures.
- Experience developing AI-powered applications and workflows.
TECHNOLOGY STACK
AI & GenAI: Python · OpenAI · Azure OpenAI · Hugging Face · Agentic AI Frameworks · LLMs · NLP · Machine Learning
Knowledge Systems: ChromaDB · Pinecone · FAISS · Vector Databases · Semantic Search
Document Processing: Docling · OCR · PDF Processing · Apache Tika · Document Intelligence
Backend: Python · FastAPI · Flask · REST APIs
Database: MySQL
Tools & Technologies: Git · Docker · JSON · CI/CD · Azure / AWS / GCP
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.
Strong Senior AI Engineer Profile with production-grade LLM and Python expertise
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Mandatory (Experience 1): Must have at least 3+ years of professional AI/ML engineering experience with demonstrated track record of delivering production-grade AI systems in real-world environments
3
Mandatory (Tech skill 1): Must have strong programming skills in Python and SQL, with hands-on ML/data libraries (scikit-learn, pandas, numpy) and deep-learning frameworks (PyTorch or TensorFlow), plus REST API design
4
Mandatory (Experience 2): Must have hands-on experience building and deploying production-grade ML/LLMs including RAG pipelines, document parsing, information extraction, and text processing on large-scale unstructured data (preprocessing, chunking, embeddings, feature engineering)
5
Mandatory (Tech skill 2): Must have strong NLP / extraction-focused ML depth — transformers, embeddings, vector databases, RAG, LLM integrations, and agentic workflows.
6
Mandatory (Tech skill 3): Must have hands-on experience with AWS (SageMaker, Bedrock, EC2, Lambda) and Azure (AI Foundry, Azure OpenAI) for model training, fine-tuning, deployment, and inference at scale
7
Mandatory (Tech skill 4): Must have experience with multi-agentic frameworks / orchestration tools (Claude Code, LangGraph, LangChain, CrewAI)
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Mandatory (Tech skill 5): Must have hands-on experience with MLOps ecosystem including experiment tracking (MLflow, Weights & Biases), model versioning/registry, automated retraining, and CI/CD (GitHub Actions, Azure DevOps, Docker, Kubernetes)
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Mandatory (Tech skill 6): Must have experience with evaluation frameworks (precision, recall, F1, field-level accuracy) and iterative model improvement, plus AI observability (Prometheus, Grafana, SLOs).
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Mandatory (Team Leadership): Must have experience leading projects or teams, managing technical deliverables, and mentoring, with strong problem-solving in ambiguous challenges
11
Mandatory (Education) - B.Tech or B.E. If graduated in BCA or BCS, they should have a Maters or Post graduation
12
Mandatory (Company): B2B Tech/Consulting/B2B Software
Location -Bangalore
Work Mode -Fully in-office, 6 days a week
Experience -3+ years in AI engineering, with LLM-based systems shipped to production
About the Role
● The AI Engineer will own systems that read, search and reason over project and tender documents.
● Inputs include large tender packages, scanned PDFs, BOQs, tables, forms and engineering drawings such as P&IDs.; Outputs should include accurate answers with source references, structured data and workflows used by estimators and project teams in live bids, planning, procurement and execution.
● The role covers taking features from initial experiments to production and owning their accuracy, latency and cost after release.
Key Responsibilities
Agents and Retrieval
● Build AI agents that plan and execute multi-step tasks using document search, tools and APIs.
● Build RAG pipelines covering ingestion, retrieval, reranking and answers with source references.
● Use agent workflows within retrieval to refine searches, collect supporting evidence and verify outputs.
Document Intelligence
● Build extraction pipelines for PDFs, scanned documents, tables and forms.
● Convert unstructured tender content into structured data that the platform can use.
Vision and Image Understanding
● Build image-understanding workflows for P&IDs;, including symbols, equipment, labels and connections.
● Locate and remove selected elements from diagram images while preserving surrounding content.
Quality and Reliability
● Create evaluation datasets and automated checks to measure accuracy and catch regressions.
● Debug failures across retrieval, agent decisions, tool calls and model outputs.
Product and Production
● Build backend services and REST APIs. ● Integrate AI features into the Workwise web application.
● Take features from experiment to production while managing reliability, latency and cost
Required Qualifications
● 3+ years of hands-on experience building AI systems, including at least one LLM-based application running in production.
● Strong Python and software engineering fundamentals.
● Experience with backend services, REST APIs, databases, authentication and frontend integration.
● Experience building applications using LLM APIs.
● Working knowledge of RAG, embeddings, retrieval and vector databases.
● Experience with tool calling, structured outputs and multi-step agent workflows.
● Working understanding of multimodal models and image processing for visual analysis and editing.
● Systematic evaluation skills: measuring results and investigating system failures.
● Ownership of implementation, testing, deployment and ongoing improvement.
Good to Have
● OCR, document layout analysis or complex table extraction.
● Computer vision experience, including object detection, segmentation or image inpainting.
● Familiarity with construction, procurement or tender documents.
● Cloud infrastructure and production monitoring.
● Working knowledge of Go.












