Senior AI Engineer

Staff Engineer - AI:

Location : India, Remote

Job Description

Egnyte is seeking an experienced Staff Software Engineer to join our Engineering department. The Engineering department builds large distributed components and services that run Egnyte's Cloud Platform. Our code serves billions of requests per day with sub-second latency in a fault-tolerant environment. We process and analyze millions of files and events daily. Some of the responsibilities for this department include Egnyte's Cloud File System, Content Classification, Content Lifecycle Management, User Behavior Analysis, Object Store, Metadata Stores, Search Systems, Recommendations Systems, Synchronization, and intelligent caching of multi-petabyte datasets. We are looking for candidates with a shared passion for building large-scale distributed systems and a keen sense for tackling complexities that come with scaling through multiple orders of magnitude.

In this role, you will (But are not limited to):

• Design and develop highly scalable and resilient cloud architecture that seamlessly integrates with on-premises systems
• Drive the team’s goals and technical direction to find and pursue technical opportunities that make Egnyte’s cloud platform more efficient
• Effectively communicate complex design and architecture details
• Understand company and industry-wide trends to help develop new technologies
• Conceptualize, develop, and implement changes that prevent key systems from becoming unreliable, under-utilized, or unsupported
• Own all aspects of critical software projects from design to implementation, QA, deployment, and monitoring

Qualifications

• BS, MS, or PhD. in Computer Science or related technical field, or equivalent practical experience
• 8-15 years of professional experience in engineering with a history of technical innovation
• Experience providing technical leadership to engineers

Bonus Qualifications (Good to Have)

• The breadth of knowledge across infrastructure domains, with the ability to reason about everything from data center machine software to database solutions to machine learning infrastructure to front-end web or mobile applications
• Demonstrated success in designing and developing large-scale, complex systems
• Expertise with multi-tenant, highly complex, cloud solutions; experience with Hybrid and/or on-premises solutions desired

About Egnyte

In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com

Dear Candidate,

We have an immediate opening with Mphasis for Senior Full Stack Engineer (Python AI).

📍 Location: Hyderabad / Bangalore

💼 Experience: 5+ Years

🏢 Employment: Permanent

⚡ Immediate Joiners Preferred

Mandatory Skills:

• Python
• Java + Spring Boot
• React.js
• MongoDB

GenAI

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.

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 NonStop io Technologies

NonStop io Technologies is a value-driven company with a strong focus on process-oriented software engineering. We specialize in Product Development and have a decade's worth of experience in building web and mobile applications across various domains. NonStop io Technologies follows core principles that guide its operations and believes in staying invested in a product's vision for the long term. We are a small but proud group of individuals who believe in the 'givers gain' philosophy and strive to provide value in order to seek value. We are committed to and specialize in building cutting-edge technology products and serving as trusted technology partners for startups and enterprises. We pride ourselves on fostering innovation, learning, and community engagement. Join us to work on impactful projects in a collaborative and vibrant environment.

Brief Description:

We're seeking an AI/ML Engineer to join our team. As AI/ML Engineer, you will be responsible for designing, developing, and implementing artificial intelligence (AI) and machine learning (ML) solutions to solve real-world business problems. You will work closely with engineering teams, including software engineers, domain experts, and product managers, to deploy and integrate Applied AI/ML solutions into the products that are being built at NonStop io. Your role will involve researching cutting-edge algorithms and data processing techniques, and implementing scalable solutions to drive innovation and improve the overall user experience.

Responsibilities

● Applied AI/ML engineering; Building engineering solutions on top of the AI/ML tooling available in the industry today. Eg: Engineering APIs around OpenAI

● AI/ML Model Development: Design, develop, and implement machine learning models and algorithms that address specific business challenges, such as natural language processing, computer vision, recommendation systems, anomaly detection, etc.

● Data Preprocessing and Feature Engineering: Cleanse, preprocess, and transform raw data into suitable formats for training and testing AI/ML models. Perform feature engineering to extract relevant features from the data

● Model Training and Evaluation: Train and validate AI/ML models using diverse datasets to achieve optimal performance. Employ appropriate evaluation metrics to assess model accuracy, precision, recall, and other relevant metrics

● Data Visualization: Create clear and insightful data visualizations to aid in understanding data patterns, model behaviour, and performance metrics

● Deployment and Integration: Collaborate with software engineers and DevOps teams to deploy AI/ML models into production environments and integrate them into various applications and systems

● Data Security and Privacy: Ensure compliance with data privacy regulations and implement security measures to protect sensitive information used in AI/ML processes

● Continuous Learning: Stay updated with the latest advancements in AI/ML research, tools, and technologies, and apply them to improve existing models and develop novel solutions

● Documentation: Maintain detailed documentation of the AI/ML development process, including code, models, algorithms, and methodologies for easy understanding and future reference.

Qualifications & Skills

● Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, or a related field. Advanced degrees or certifications in AI/ML are a plus

● Proven experience as an AI/ML Engineer, Data Scientist, or related role, ideally with a strong portfolio of AI/ML projects

● Proficiency in programming languages commonly used for AI/ML. Preferably Python

● Familiarity with popular AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, etc.

● Familiarity with popular AI/ML Models such as GPT3, GPT4, Llama2, BERT etc.

● Strong understanding of machine learning algorithms, statistics, and data structures

● Experience with data preprocessing, data wrangling, and feature engineering

● Knowledge of deep learning architectures, neural networks, and transfer learning

● Familiarity with cloud platforms and services (e.g., AWS, Azure, Google Cloud) for scalable AI/ML deployment

● Solid understanding of software engineering principles and best practices for writing maintainable and scalable code

● Excellent analytical and problem-solving skills, with the ability to think critically and propose innovative solutions

● Effective communication skills to collaborate with cross-functional teams and present complex technical concepts to non-technical stakeholders

Role Overview 

We are looking for an AI Engineer to design, build, and ship production AI systems, including agentic AI applications, for enterprise clients. This is a hands-on engineering role: you will write production code, build and evaluate models and agents, and work closely with architects and product teams to take solutions from prototype to scale. 

Key Responsibilities 

Design and build agentic AI systems: agent workflows, tool/function-calling, memory, and human-in-the-loop patterns. Build and productionise RAG pipelines, prompt-based applications, and LLM integrations across providers. Develop and maintain data and ML pipelines: feature engineering, model training, evaluation, and monitoring. Integrate AI systems with enterprise applications (CRMs, ERPs, ITSM tools) via APIs, events, and MCP-based tool servers. Implement guardrails, prompt-injection defences, and evaluation frameworks to keep AI systems safe and reliable in production. 

Write clean, tested, production-grade code and participate actively in code and design reviews. 

Collaborate with architects, product managers, and delivery teams to translate requirements into working AI solutions. Troubleshoot and optimise AI systems for accuracy, latency, and cost in production. 

Required Qualifications 

8–12 years of hands-on software engineering experience, with a strong, unbroken technical track record. Hands-on experience building and shipping AI/ML systems in production, not just POCs. 

Practical experience with agentic AI systems and at least one major agent framework (LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, Bedrock Agents/Strands, or Semantic Kernel). 

Experience with LLM/GenAI systems: RAG pipelines, prompt engineering, structured outputs, and tool calling across providers. 

Strong Python skills (TypeScript/Node.js a plus), with production-grade testing, CI/CD, and API design practices. Working knowledge of ML fundamentals: model evaluation, feature engineering, and experimentation. Cloud-native experience on AWS and/or Azure: containers, serverless, event backbones, and vector databases. Understanding of LLM safety and reliability practices: guardrails, prompt-injection defences, and observability. 

Job Summary

We are looking for an experienced AI/ML Engineer to design, develop, deploy, and maintain machine learning and AI solutions that address complex business problems. The ideal candidate should have strong hands-on experience in Python, Machine Learning, Generative AI, LLMs, and AI/ML deployment, with the ability to work across the complete AI/ML lifecycle.

Key Responsibilities

• Design, develop, and deploy scalable Machine Learning and AI models for real-world business use cases.
• Build and optimize ML pipelines covering data preparation, feature engineering, model development, evaluation, and deployment.
• Develop solutions using Generative AI, Large Language Models (LLMs), NLP, and deep learning.
• Work with LLMs, prompt engineering, embeddings, vector databases, and Retrieval-Augmented Generation (RAG) architectures.
• Integrate AI/ML models with enterprise applications and APIs.
• Fine-tune and evaluate ML/LLM models based on business requirements.
• Implement MLOps practices for model versioning, deployment, monitoring, and continuous improvement.
• Collaborate with Data Scientists, Software Engineers, Architects, Product Managers, and business stakeholders.
• Conduct model performance evaluation, optimization, and troubleshooting.
• Ensure AI solutions meet requirements around security, scalability, reliability, responsible AI, and data privacy.
• Stay current with emerging AI/ML technologies, frameworks, and industry best practices.

Required Skills

• Strong programming experience in Python.
• Strong understanding of Machine Learning algorithms, statistics, and data structures.
• Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or equivalent.
• Experience with Generative AI and LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, or open-source models.
• Strong knowledge of Prompt Engineering, RAG, embeddings, vector databases, and AI agents.
• Experience with NLP, deep learning, or computer vision is an advantage.
• Experience developing and consuming REST APIs and microservices.
• Working knowledge of SQL and NoSQL databases.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Understanding of Docker, Kubernetes, CI/CD, and MLOps.
• Familiarity with Git and modern software development practices.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
• 4 years of relevant experience in AI/ML engineering or a related field.
• Experience building and deploying production-grade AI/ML solutions.
• Enterprise application development experience.
• Experience with Azure OpenAI, AWS Bedrock, Vertex AI, or similar managed AI platforms.
• Experience with LangChain, LlamaIndex, Semantic Kernel, or comparable AI frameworks is a plus.
• Experience with AI/ML model monitoring, evaluation, and optimization.

What You Bring

• Strong problem-solving and analytical skills.
• Ability to translate business requirements into practical AI/ML solutions.
• Strong software engineering and debugging capabilities.
• Ability to work independently as well as collaboratively in a cross-functional environment.
• Good communication skills with the ability to explain complex AI concepts to technical and non-technical stakeholders.

Keywords

AI Engineer | ML Engineer | Machine Learning | Generative AI | LLM | Python | NLP | Deep Learning | RAG | Prompt Engineering | AI Agents | Azure OpenAI | AWS Bedrock | MLOps | TensorFlow | PyTorch | Scikit-learn | Vector Database | Cloud AI

Location: Gurugram

Work mode: Hybrid

Hiring for AI Engineer

Exp: 6 - 12 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 or Typescript is a MUST

Min 2.5 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 Overview:

As an AI Executor/AI Automation Engineer, you will be responsible for designing and integrating AI capabilities into production systems using Python and key ML libraries. This role requires a strong backend development foundation and a proven track record of deploying AI use cases using tools like TensorFlow, Keras, or OpenAI APIs. You'll work cross-functionally to deliver scalable AI-driven solutions.

Key Responsibilities:

• Design and develop backend solutions using Python, with a focus on AI-driven features.
• Implement and integrate AI/ML models using tools like OpenAI, Hugging Face, or Lang Chain.
• Use core Python libraries (NumPy, Pandas, TensorFlow, Keras) to process data, train, or implement models.
• Translate business needs into AI use cases and deliver working solutions.
• Collaborate with product, engineering, and data teams to define integration workflows.
• Develop REST APIs and micro services to deploy AI components within applications.
• Maintain and optimize AI systems for scalability, performance, and reliability.
• Keep pace with advancements in the AI/ML landscape and evaluate tools for continuous improvement.

Required Skills & Qualifications:

• 2+ years of professional experience as an AI/ML Engineer, including strong backend development expertise in Python.
• Proficiency in libraries such as NumPy, Pandas, TensorFlow, and Keras
• Practical exposure to AI platforms/APIs (e.g., OpenAI, LangChain, Hugging Face)
• Solid understanding of REST APIs, micro services, and integration practices
• Ability to work independently in a remote setup with strong communication and ownership
• Excellent problem-solving and debugging capabilities
• Experience with the MERN stack will be an added advantage.

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.