AI Engineer at Vertexcover Labs · Remote only · 1 - 6 years · ₹12L - ₹32L / yr · Profitable · Remote only · Posted 15 Jul 2026
Python
Go Programming (Golang)
Rust
JavaAI Engineer — Vertexcover Labs
Who We Are
Vertexcover Labs is an employee-focused, engineer-run software studio. We partner with fast-growing, funded startups around the world—Rephrase.ai, Dhiwise, Dunzo, Dubdub, Xapo, Arintra etc.—to crack their toughest engineering problems. Everyone is an individual contributor; no management layers. Engineers choose the projects they work on, see each project's P&L, and share directly in the profits.
Whether it's building multi-agent systems for production, scaling ML pipelines across GPU clusters, or shipping RAG-powered products that end-users rely on—we solve hard AI problems for real companies.
A Few Problems We Are Currently Working On
- AI Agents Test-authoring agents that convert natural language into e2e tests.
- Ad-performance agents that learn what works for your brand and generate winning creatives automatically.
- Scale + MLOps Optimise ML pipelines and fix autoscaling by applying queuing theory while juggling CPU / GPU memory contention.
- RAG & Knowledge Systems Design and deploy retrieval-augmented generation pipelines—chunking strategies, embedding models, reranking, and evaluation loops.
- AI Video & Image Processing Build rendering pipelines, diffusion-model integrations, and real-time video processing at scale. You'll own at least one project like these—design, build, iterate.
Signals You're Probably the Right Fit
- Strong in at least one other language (Python, Go, Rust, TypeScript, Java …); happy to learn more.
- First principle understanding of how LLMs, embeddings, vector databases and AI Agents work
- Evidence of shipping real AI-powered software—OSS, side projects, or production features.
- Comfortable navigating the fast-moving AI landscape—papers, new model releases, evolving APIs.
- Clear written & spoken communication; async collaboration is our default.
- Self-directed—you ask for context, not permission.
How We Operate
- Project choice. Engineers vote on which engagements we take.
- Stack agnostic. We pick tools that fit the job, not the résumé.
- Pragmatic craftsmanship. Durable design, no gold-plating.
- Transparent economics. Know what your work is worth, share in the profits.
- Remote-native. Async by default; sync when it helps.
Hiring Process (Lean & Human)
- 2–3 technical deep-dives with future teammates.
- 30-minute culture chat.
- Offer. No LeetCode marathons, no trick puzzles.
We read every application and reply to all candidates.
Shubham Vishwakarma
Full Stack Developer - Averlon
About Vertexcover Labs
About
About Us
At Vertexcover Labs, we're on a mission to revolutionize the way real-world problems are tackled using Generative AI. We pride ourselves on delivering cutting-edge solutions for some of the leading consumer-facing companies out there. Our collaborations with top names such as Invideo, Rephrase, Dunzo, Xapo, Dubdub, and Madmen have empowered us to drive AI-driven transformations that make a tangible impact.
As an employee-first startup, Vertexcover Labs is deeply committed to the happiness, growth, and continuous learning of our team. Our unique cultural values set us apart from others in the industry, creating an environment where innovation flourishes and ideas come to life.
Why Join Us?
- Tackle Hard Problems: Engage with some of the most challenging issues in the AI domain and see your solutions come to life.
- Choose Your Projects: Gain the autonomy to select projects that excite and inspire you, aligning with your personal and professional growth aspirations.
- Profit Sharing: Benefit from our profit-sharing model that recognizes and rewards your contributions to our collective success.
At Vertexcover Labs, we believe in creating a workspace that not only fuels creativity and innovation but also values and uplifts each member. If you're passionate about making a difference with Generative AI and thrive in a dynamic, supportive environment, we’d love to hear from you. Join us in shaping the future!
Connect with the team
Company social profiles
Similar jobs (10)
Hiring for AI Engineer
Exp: 5 - 10 yrs
Edu : BE/B.Tech/MCA
Work Location : Pune / Mumbai
Skill Set:
Total experience ranging from 5–10 years in software engineering/AI roles
Min 5 years strong programming experience in Python is a MUST
Min 3.5 years hands-on experience in AI with LLMs, RAG pipelines, and AI frameworks
2+ years shipping LLM systems in production
Experience with cloud platforms (AWS/Azure/GCP)
Role: AI Developer
Experience: 3–4 Years
Employment Type: Full-Time
Location: Goregaon, Mumbai
About the Role
We are looking for an experienced AI Developer with 3–4 years of software development experience and strong hands-on exposure to Generative AI, AI Agents, Copilots, and AI-powered application development.
The candidate will be responsible for building production-ready AI solutions, developing agentic workflows, modernizing legacy applications, and integrating LLM capabilities into enterprise applications.
Key Responsibilities
- Design, develop, and deploy AI Agents and agentic workflows for enterprise use cases.
- Build AI Copilots and LLM-powered applications using modern AI frameworks and APIs.
- Develop RAG-based applications using embeddings, vector databases, and enterprise data.
- Work on legacy application migration and modernization, leveraging AI-assisted development and code transformation techniques.
- Analyze legacy codebases and design strategies for AI-driven migration, refactoring, and modernization.
- Integrate LLMs with enterprise applications, APIs, databases, and third-party systems.
- Implement tool calling, function calling, multi-agent workflows, and workflow automation.
- Perform prompt engineering, context optimization, model evaluation, and AI application testing.
- Take ownership of AI solutions from POC and prototyping through production deployment.
- Collaborate with product managers, architects, and engineering teams to convert business requirements into scalable AI solutions.
- Stay updated with emerging technologies in Generative AI, Agentic AI, LLMs, and AI-assisted software development.
Required Skills
- 3–4 years of professional software development experience.
- Strong proficiency in Python and/or JavaScript/TypeScript.
- Hands-on experience developing Generative AI / LLM-based applications.
- Strong understanding of AI Agents, RAG, Prompt Engineering, LLM APIs, and embeddings.
- Experience with frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or equivalent.
- Experience working with REST APIs, databases, Git, and cloud environments.
- Hands-on experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, or equivalent.
- Good understanding of software architecture, debugging, testing, and deployment practices.
Good to Have
- Experience with Microsoft Copilot / Copilot Studio.
- Experience working with Claude, OpenAI, Gemini, Azure OpenAI, or open-source LLMs.
- Experience in legacy application migration, modernization, or code conversion.
- Knowledge of Azure AI / AWS / Google Cloud AI services.
- Experience with MCP, multi-agent systems, tool calling, and AI orchestration.
- Experience building enterprise-grade AI solutions with focus on security, scalability, and performance.
Job Description – AI Engineer (End-to-End Development & Deployment)
Role Summary
We are looking for an AI Engineer with hands-on experience in designing, developing, deploying, and maintaining Generative/Agentic AI solutions in production. The ideal candidate should have end-to-end ownership of AI applications, from development to deployment, monitoring, and optimization.
Key Responsibilities
● Design, build, and deploy Generative/Agentic AI solutions.
● Develop applications using LLMs, RAG, AI agents, and vector databases.
● Build scalable APIs and integrate AI solutions with enterprise applications.
● Implement CI/CD pipelines, containerization, and MLOps best practices.
● Monitor, optimize, and maintain production AI systems.
● Collaborate with cross-functional teams to deliver business-driven AI solutions.
Required Skills
● Strong programming skills in Python.
● Experience with vector databases (e.g., Pinecone, FAISS, ChromaDB) and graph memory systems
● Knowledge of atleast one agent development framework: Google ADK (preferred), LangChain/LangGraph/LlamaIndex, CrewAI
● Experience with LLMs, RAG, GenAI, AgenticAI Agents
● Hands-on experience with FastAPI, and REST APIs.
● Knowledge of Docker, Kubernetes, Git, CI/CD.
● Experience with AWS, Azure, or GCP.
● Experience with security compliance, monitoring and observability tools such as AWS CloudWatch, Azure Monitor, Google Cloud Monitoring.
PythonJob Description:
We are looking for a hands-on AI Engineer with experience in Generative AI and Agentic AI to build and deploy production-ready AI solutions.
Key Responsibilities:
- Develop and deploy GenAI and Agentic AI applications.
- Build RAG pipelines, LLM workflows, and AI agents.
- Develop solutions using Python, LangChain, LangGraph, LlamaIndex, or similar frameworks.
- Implement tool calling, context retrieval, and LLM orchestration.
- Integrate AI solutions with APIs and cloud platforms.
- Work with AWS/Azure/GCP, Docker, and CI/CD.
Required Skills:
- Strong Python programming skills.
- 3+ years of GenAI/Agentic AI experience.
- RAG and LLM orchestration.
- LangChain / LangGraph / LlamaIndex / AutoGen / CrewAI / Semantic Kernel.
- MCP and A2A knowledge.
- Cloud, APIs, Docker, and CI/CD experience.
Preferred Experience:
Hands-on experience building and deploying production-ready AI solutions.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Amazon Web Services (AWS)Senior Generative AI Engineer
Employment Type: Permanent with VDart Digital
Work Location: Marathalli, Bengaluru
Job Description
We are seeking a highly skilled Senior Generative AI Engineer with strong expertise in designing, developing, and deploying enterprise-scale AI solutions using Large Language Models (LLMs) and modern Generative AI frameworks. The ideal candidate should have hands-on production experience building scalable GenAI applications, AI agents, autonomous workflows, and Retrieval-Augmented Generation (RAG) systems in cloud-native environments.
This role requires deep technical expertise in LLM orchestration, AI application architecture, prompt engineering, vector databases, MLOps, and production deployment of AI systems. Candidates should have proven experience delivering real-world AI solutions in enterprise environments with strong exposure to cloud platforms and DevOps practices.
Key Responsibilities
- Design, build, and deploy enterprise-grade Generative AI applications using Large Language Models (LLMs).
- Develop intelligent AI agents and autonomous workflows using frameworks such as LangChain, CrewAI, LangGraph, AutoGen, or similar agentic AI frameworks.
- Implement and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and semantic search technologies.
- Work extensively on prompt engineering, tool calling, memory management, agent orchestration, and multi-agent systems.
- Integrate and manage LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, or similar foundation models.
- Develop scalable AI services and APIs using Python and FastAPI.
- Build production-ready AI solutions with high availability, scalability, monitoring, and observability.
- Deploy and manage AI applications in cloud-native environments using Docker and Kubernetes.
- Collaborate with Data Science, ML Engineering, and DevOps teams to operationalize AI solutions.
- Implement CI/CD pipelines and automated deployment processes for AI workloads.
- Monitor model performance, latency, reliability, and operational efficiency in production environments.
- Ensure AI solutions follow enterprise security, governance, and responsible AI standards.
- Evaluate and adopt emerging Generative AI tools, frameworks, and models.
Required Skills
Generative AI & LLM Expertise
- Strong hands-on experience with Generative AI and Large Language Models (LLMs).
- Production-level experience building and deploying GenAI applications.
- Expertise in LangChain, CrewAI, LangGraph, AutoGen, or similar frameworks.
- Experience with AI agents, autonomous workflows, and multi-agent architectures.
- Strong understanding of prompt engineering, embeddings, model evaluation, and LLM orchestration.
- Experience integrating OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, or similar models.
RAG & Vector Databases
- Strong experience implementing RAG pipelines and semantic retrieval systems.
- Experience with vector databases such as Pinecone, Weaviate, ChromaDB, FAISS, or Milvus.
- Understanding of chunking strategies, embeddings, indexing, reranking, and retrieval optimization.
Python & AI Development
- Strong proficiency in Python.
- Experience with FastAPI for AI service and API development.
- Experience with AI/ML libraries and data processing tools such as Pandas and NumPy.
Cloud & Production Deployment
- Mandatory production experience on at least one cloud platform:
- Microsoft Azure
- Experience deploying scalable AI applications in enterprise production environments.
- Hands-on experience with Docker, Kubernetes, Jenkins, Terraform, and CI/CD pipelines.
- Strong understanding of MLOps, AI deployment lifecycle, monitoring, and observability.
Engineering & Operational Excellence
- Strong understanding of software engineering best practices.
- Experience with Git, version control, automated testing, and release management.
- Experience building secure, scalable, and high-performance AI solutions.
- Ability to troubleshoot production AI systems and optimize performance.
Preferred Skills
- Experience with AI observability and evaluation frameworks.
- Exposure to fine-tuning, PEFT, LoRA, or model optimization techniques.
- Experience with enterprise AI governance and responsible AI practices.
- Knowledge of distributed AI systems and scalable inference architectures.
- Familiarity with AI security and compliance standards.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- 3–8 years of overall software engineering experience.
- Minimum 3+ years of hands-on experience in Generative AI and LLM-based application development,
- Proven track record of delivering enterprise-scale AI solutions in production environments.
- Strong communication and stakeholder management skills.
Python
Machine Learning (ML)Job Summary/ Job Opportunity:
This is an excellent opportunity for an ideal candidate with a high level of technical proficiency and meeting the below mentioned criteria -- • Strong experience in Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs). • Hands-on experience building and deploying production-grade solutions using Azure OpenAI, OpenAI, LangChain, LangGraph, Semantic Kernel, LlamaIndex, and Agentic AI frameworks. • Strong expertise in Python, API development, microservices, and cloud-native architectures. • Experience designing and implementing RAG solutions, vector databases, embeddings, knowledge retrieval systems, and AI copilots. • Experience with Azure cloud services, MLOps, CI/CD pipelines, monitoring, and model lifecycle management. • Strong understanding of AI governance, responsible AI, security, compliance, and model evaluation frameworks. • Ability to lead technical discussions, provide architectural recommendations, mentor team members, and interact with business stakeholde
Key Objectives and Major Responsibilities:
• Design, develop, and implement scalable AI/ML and Generative AI solutions for enterprise applications. • Lead development of intelligent applications leveraging LLMs, RAG pipelines, AI agents, and document intelligence solutions. • Collaborate with business stakeholders, architects, and product teams to translate business requirements into technical solutions. • Design and optimize data pipelines, vector search solutions, embeddings, and retrieval mechanisms. • Build and maintain REST APIs, microservices, and cloud-native AI applications. • Ensure best practices in coding standards, performance optimization, security, scalability, and maintainability. • Drive AI solution deployment using MLOps practices, CI/CD pipelines, monitoring, and observability frameworks. • Perform code reviews, mentor junior developers, and contribute to capability building within the team
Key Capabilities and Competencies:
Knowledge, Skills, Qualification and Experience
• Degree in B.Tech/M.Tech (Computer Science/IT/Data Science) or related discipline preferred, with 3–4 years of relevant experience in AI/ML, GenAI and total 5-7 years of experience. • Proficiency in Python and hands-on experience with ML libraries (scikit-learn, TensorFlow, PyTorch) and GenAI frameworks/tools. • Strong understanding of machine learning, deep learning, LLMs, prompt engineering, and techniques like RAG and fine-tuning. • Experience with data processing, embeddings, vector databases, APIs, and building scalable AI driven applications. • Good communication skills, ability to work on multiple projects, and eagerness to learn and adapt to evolving AI technologies.
Machine Learning (ML)
Deep LearningPython🚀 WE’RE HIRING | AI/ML GENERATIVE AI ENGINEER
📍 Location: Remote
💼 Experience: 5+ Years
🔄 Position: Contract – Extendable
🔹 ROLE HIGHLIGHTS
➤ Build and deploy AI/ML amp; Generative AI solutions
➤ Develop LLM, RAG, NLP, Recommendation amp; Predictive solutions
➤ Work on AI Agents, Chatbots, Computer Vision amp; Content Intelligence
➤ Build ML models using PyTorch, TensorFlow, Keras amp; Scikit-learn
➤ Develop RAG solutions using LangChain, LlamaIndex, FAISS/Milvus
➤ Integrate OpenAI, Azure OpenAI, AWS Bedrock, Vertex AI amp; Hugging Face
➤ Build scalable AI APIs using Python, FastAPI/Flask/Django
➤ Contribute to Private AI amp; Smart Agentic Systems
⚙️ MUST-HAVE SKILLS
◆ Python – 3+ years
◆ AI/ML – 5+ years
◆ Generative AI – 2+ years
◆ LLMs, RAG, Embeddings , Transformers
◆ ML/DL, NLP amp; Predictive Analytics
◆ Cloud AI Platforms – Azure / AWS / GCP
◆ AI/ML Deployment | MLOps
Interview Process - F2F Round at Pune Location
PythonJob Description – Python & Generative AI Engineer
Python & Generative AI Engineer
Location: Bangalore, India
Experience: 4+ Years
Employment Type: Full-time
Job Summary
We are looking for an experienced Python & Generative AI Engineer with 4+ years of software development experience and strong hands-on expertise in Python, LLMs, Generative AI, and AI application development.
The ideal candidate should be comfortable building production-grade AI solutions, integrating LLMs with enterprise applications, and developing scalable APIs and services using Python.
Key Responsibilities
- Design, develop, and deploy Generative AI applications using Python and modern AI/ML frameworks.
- Work with Large Language Models (LLMs) such as GPT, Claude, Gemini, Llama, or similar models.
- Develop RAG (Retrieval-Augmented Generation) pipelines using vector databases and embedding models.
- Build AI-powered applications using frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent.
- Develop scalable REST APIs and backend services using FastAPI, Flask, or Django.
- Integrate LLM APIs, prompt engineering, function/tool calling, and structured outputs into enterprise applications.
- Work with vector databases such as FAISS, Pinecone, Weaviate, Milvus, or Azure AI Search.
- Implement document processing, chunking, embeddings, semantic search, and knowledge retrieval solutions.
- Evaluate LLM responses for accuracy, relevance, hallucination, latency, and cost.
- Build and maintain production-ready AI pipelines with appropriate monitoring, logging, security, and error handling.
- Collaborate with data scientists, ML engineers, software engineers, and business stakeholders to deliver AI solutions.
- Write clean, reusable, testable, and well-documented Python code.
- Participate in architecture discussions, code reviews, testing, deployment, and production support.
Required Skills
- 4+ years of experience in software/Python development.
- Strong proficiency in Python and object-oriented programming.
- Hands-on experience with Generative AI and LLM-based applications.
- Experience with OpenAI/Azure OpenAI, Anthropic, Google Gemini, or open-source LLMs.
- Strong understanding of Prompt Engineering and LLM application patterns.
- Experience implementing RAG pipelines.
- Knowledge of embeddings, vector databases, semantic search, and document retrieval.
- Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.
- Strong experience developing REST APIs using FastAPI/Flask/Django.
- Familiarity with Git, CI/CD, Docker, and cloud platforms such as AWS, Azure, or GCP.
- Good understanding of SQL and databases.
- Strong problem-solving and communication skills.
Good to Have
- Experience with AI agents / Agentic AI and tool/function calling.
- Experience with multi-agent frameworks.
- Knowledge of MLOps/LLMOps and model evaluation.
- Experience with Kubernetes and containerized deployments.
- Knowledge of NLP, machine learning, or deep learning.
- Experience with Azure AI, AWS Bedrock, Amazon SageMaker, or Google Vertex AI.
- Understanding of responsible AI, data privacy, and LLM security.
Education
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
Python
JavascriptLocation: Hyderabad, India (home base), deployed at client sites in India. Occasional Middle East exposure possible.
About the Role
You will work as a senior AI engineer who embeds inside a customer's business. Your job is to learn how the business makes money, find the highest value problem, and build a working system that solves it.
Four behaviors define this role:
- Go where the work happens. You work onsite with the customer, in the room where decisions are made.
- Show working software early. You build a prototype in days, not a document in weeks.
- One person owns the outcome. You are the single point of accountability for the result.
- Stay after go-live. You keep running and improving the system after launch.
You are the single point of accountability. You are not a solo builder. A full KnackLabs engineering team in Hyderabad builds and runs the production systems behind you.
This role involves extended onsite deployments at client locations in other cities, sometimes up to six months at a stretch. Please apply only if you are ready for this way of working.
What you'll own
- Discovery - Learn how the customer makes money. Find the highest value problem to solve first.
- The prototype - Build a working prototype fast, using real or sample data, to prove the idea.
- The roadmap - Decide what to build, in what order, and set clear success measures tied to business outcomes.
- The build - Design and ship the production system with the Hyderabad engineering team. This includes data integration, agents, retrieval, and evaluations.
- The client relationship - Be the trusted technical contact for the customer, from engineers to senior leaders.
- Go live and after - Deploy the system, watch how it performs, fix problems, and improve it over time.
- Feedback to the product - Share what you learn in the field so the vendor's product and our internal tools get better.
What we are looking for
- Around 4 or more years of software engineering experience, including customer-facing or client delivery work.
- Strong programming skills in Python. Working knowledge of TypeScript or JavaScript.
- A full-stack development experience with strength in backend technologies.
- Production experience with large language models, including prompt engineering and agent development.
- You build with AI coding tools like Claude Code or Codex as your default way of working, and you have shipped real apps or agents this way.
- Experience building retrieval-augmented generation (RAG) systems: chunking, embeddings, vector databases, retrieval, and reranking.
- Experience building and deploying AI systems.
- Experience integrating with APIs and enterprise systems.
- Experience with at least one cloud platform (AWS, Azure, or GCP).
- Clear communication. You can explain a technical choice to an engineer and to a business leader.
- High ownership and comfort with ambiguity. You can take an unclear problem and turn it into a plan.
- Willingness to work onsite at client locations in India for extended periods, and to travel as the work needs.
Nice to have
- Experience with on-premises or private cloud (VPC) deployments.
- Experience with observability and tracing tools such as LangSmith or Braintrust.
- Experience with data engineering and pipelines.
- A history of side projects, open source contributions, or products you shipped end-to-end.
- Experience in embedded or forward-deployed roles before.
- Experience working at a consulting or professional services firm in a client-facing delivery role.
Stack and tools
- Languages: Python and TypeScript.
- Models: Claude and other frontier or open-source models, chosen to fit the customer.
- AI patterns: RAG, agents, prompt engineering, and evaluations.
- Vector and retrieval: vector databases and retrieval pipelines.
- Cloud: AWS, Azure, or GCP, on public or private cloud.
- Integration: REST APIs and enterprise system connectors.
Strong AI Engineer / Machine Learning Engineer profiles.
2
Mandatory (Experience 1) – Must have minimum 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.
3
Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.
4
Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.
5
Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.
6
Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.
7
Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.
8
Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.
9
Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.
10
Mandatory (Age) - Candidate's Age should be below 28 Years
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon