AI Solution Engineer (.NET and Python)

Principal Software Engineer

Company Summary :

As the recognized global standard for project-based businesses, Deltek delivers software and information solutions to help organizations achieve their purpose. Our market leadership stems from the work of our diverse employees who are united by a passion for learning, growing and making a difference. At Deltek, we take immense pride in creating a balanced, values-driven environment, where every employee feels included and empowered to do their best work. Our employees put our core values into action daily, creating a one-of-a-kind culture that has been recognized globally. Thanks to our incredible team, Deltek has been named one of America's Best Midsize Employers by Forbes, a Best Place to Work by Glassdoor, a Top Workplace by The Washington Post and a Best Place to Work in Asia by World HRD Congress. www.deltek.com

Position Responsibilities :

About the Role 

We are seeking a highly motivated AI Solutions Engineer to join Deltek’s growing AI Center of Excellence team to design, develop, deploy, and optimize internal Artificial Intelligence and Machine Learning solutions that solve complex business challenges. The ideal candidate combines deep expertise in AI, machine learning, Generative AI, Large Language Models (LLMs), SLMs, software engineering, cloud computing, and MLOps/LLMOps to build scalable, production-grade AI applications. 

The AI Solutions Engineer will collaborate with AI data scientists, architects, and engineering teams to deliver innovative AI-driven solutions while ensuring security, scalability, governance, and operational excellence. This role reports to the Senior AI Solutions Architect. 

Key Responsibilities 

AI & Machine Learning Development 

• Design, build, train, evaluate, and deploy machine learning and deep learning models. 
• Develop Generative AI solutions using Large Language Models (LLMs) such as GPT, Claude, Gemini, Llama, and Mistral. 
• Implement Retrieval-Augmented Generation (RAG), prompt engineering, fine-tuning, and AI agent frameworks. 
• Build NLP, recommendation systems, forecasting, predictive analytics, and intelligent automation solutions. 
• Optimize model performance, scalability, latency, and cost. 

Software Engineering & Solution Development 

• Develop production-grade AI applications using Python and modern software engineering practices. 
• Build APIs, microservices, and AI-powered enterprise applications. 
• Integrate AI services with enterprise systems, business applications, and data platforms. 
• Apply coding standards, automated testing, CI/CD, and version control best practices. 

MLOps & AI Operations 

• Design and implement MLOps pipelines for model development, deployment, monitoring, and lifecycle management. 
• Automate model training, validation, testing, and deployment processes. 
• Monitor model performance, data drift, hallucinations, and operational metrics. 
• Support continuous improvement and reliability of AI platforms. 

Cloud & Platform Engineering 

• Develop AI solutions on Azure, AWS, or Google Cloud platforms. 
• Leverage cloud-native AI services, containerization, Kubernetes, and serverless technologies. 
• Build scalable architectures supporting enterprise AI workloads and real-time inference. 

AI Governance & Security 

• Ensure compliance with Responsible AI, security, privacy, and regulatory requirements. 
• Implement model governance, explainability, bias mitigation, and risk management practices. 
• Maintain standards for secure design, deployment, and operation of AI solutions. 

Required Qualifications 

Education 

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related technical field. 

Experience 

• 5+ years of software engineering or machine learning development experience. 
• 2+ years of hands-on experience developing and deploying Agentic AI, Generative AI or AI/ML solutions in production environments. 

Technical Skills 

Programming & Engineering 

• Strong expertise in Python. 
• Experience with Java, ReactJS, JavaScript, or similar programming languages. 
• Solid understanding of algorithms, data structures, APIs, and software design principles. 

Artificial Intelligence & Machine Learning 

• Machine Learning and Deep Learning concepts and frameworks. 
• Model training, evaluation, optimization, and deployment. 

Generative AI 

• Large Language Models (LLMs) & SLMs 
• Prompt Engineering 
• Retrieval-Augmented Generation (RAG) 
• AI Agents and Agentic Workflows 
• Fine-tuning and model customization 
• Vector embeddings and semantic search 

Frameworks & Tools 

• PyTorch, TensorFlow, Scikit-learn 
• LangChain, LlamaIndex, Semantic Kernel, MCP, A2A and Transformers 
• FastAPI, Flask 

Data & Analytics 

• SQL and NoSQL databases 
• Data pipelines, ETL, and data modeling 
• Experience with AWS, Azure and Google 

MLOps & DevOps 

• MLflow, Kubeflow, Azure ML, SageMaker 
• Docker and Kubernetes 
• Git, GitHub, Azure DevOps, Jenkins 
• CI/CD automation and model monitoring 

Cloud Platforms 

• AWS (preferred) 
• AWS Bedrock or Azure OpenAI Service 
• AWS SageMaker 
• Google Vertex AI 

Preferred Qualifications 

• Experience designing enterprise-scale AI platforms and products.  
• Knowledge of multi-agent architectures and autonomous AI systems.  
• Experience with vector databases such as Pinecone, Snowflake Cortex, Pgvector, Weaviate, Chroma, or Azure AI Search.  
• Understanding of AI governance, compliance, and Responsible AI frameworks.  
• Relevant certifications in Azure AI, AWS Machine Learning, or Google Cloud AI.

Hiring for AI Engineer

Exp: 5 - 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)

EMBEDDED AI ENGINEERING POD

AI Implementation Engineer Role

Level: AI Implementation Engineer Senior / Advanced - 6+ years

Practice: Wissen GenAI

Locations: Mumbai / Bengaluru / New York - hybrid, embedded with delivery teams

Reports to: EMBEDDED AI PRACTICE Senior AI Engineering Specialist (Architect); Wissen GenAI Program Lead

Embedded inside enterprise delivery teams, you work closely with global, cross-regional teams to turn prioritized GenAI use cases into production software - building, integrating, and hardening Azure-based AI solutions and accelerating adoption within the teams you join.

You deliver production software and help the teams you join work faster.

As an embedded AI Implementation Engineer, you help convert prioritized use cases into shipped, governed, measurable software.

Key responsibilities

1. Build and ship.

Implement GenAI features end to end on Azure - RAG pipelines, agents, APIs, and UI integrations - against enterprise systems and data.

2. Embed and enable.

Work inside the delivery pods: pair with their engineers, remove blockers, and transfer GenAI skills so adoption sticks after you move on.

3. Productionize.

Add evaluation, observability, guardrails, caching, and CI/CD so prototypes become reliable, cost-efficient services.

4. Integrate securely.

Connect to enterprise data with correct access control, secrets management, and compliance with enterprise security standards and handling of sensitive data.

5. Iterate on quality.

Use evaluation results and user feedback to improve grounding, accuracy, latency, and cost.

6. Measure.

Track delivery and quality metrics that roll up to the program's targets.

Must-have qualifications

• 6+ years in software engineering, with 2+ years building GenAI/LLM applications in production.
• Strong Python (incl. async) and Java (the primary enterprise application stack; Spring a plus); solid API and systems design.
• Azure GenAI hands-on: Azure OpenAI, Azure AI Foundry, Azure AI Search for RAG, Azure AI Document Intelligence (IDP), and Prompt Flow.
• Agent frameworks: Microsoft Agent Framework / Semantic Kernel / AutoGen (or LangChain / LangGraph) and tool / function calling.

Preferred

• RAG fundamentals: embeddings, chunking, vector search, reranking, and grounding.
• Data platforms: Snowflake including Cortex AI (Cortex Search, LLM functions) and SQL, for accessing and grounding on enterprise data.
• Prompt engineering as versioned code; building and running evaluations.
• DevOps: Azure DevOps / GitHub Actions, Docker, AKS / Azure Functions, and observability.
• Financial services or other regulated environments.
• Front-end (React) for AI-assisted UX; streaming and token level operations.
• Azure AI Content Safety and responsible-AI practices.
• Certification: Azure AI Engineer Associate.

What success looks like - first 6 to 12 months

• Multiple GenAI features shipped to production within the embedded delivery pods.
• Measurable adoption and productivity uplift in the teams you support.
• Reusable components adopted from the architects' reference framework.
• Clear contribution to faster time-to-market and lower defect rates.

Software Engineer II to join Planview’s Keyedin team.

Planview is an enterprise software company focused on portfolio and work management, helping organizations plan, prioritize, and deliver work across strategy, teams, and technology. Its product portfolio spans project and portfolio management (PPM), enterprise agile planning, product portfolio management, and work management tools — including offerings like AdaptiveWork, Planview PPM Pro, ProjectPlace, Planview Viz, and Deliver (One2Team), plus its ProjectAdvantage (formerly Sciforma) product for project and resource management. The company serves a wide range of industries, from financial services to technology to government, helping large organizations connect strategy to execution and manage complex portfolios of projects, products, and resources.

About the Role:

You’ll work on a product that combines legacy and modern technologies, contributing across the full stack while helping shape future platform integrations, connectors, and AI-powered capabilities. You’ll also work directly on customer-facing tickets and real-world product challenges, gaining hands-on exposure to the application and its technology stack from day one.

What You’ll Work On

• Customer-facing development and product enhancements
• Platform integrations and connector development
• Cloud technologies and AI-enabled capabilities
• Maintenance and modernization of existing product functionality
• Collaboration on new technologies as the platform evolves

Must-Have Skills

• C#/.NET, MVC, VB.NET, Web API, and Dapper
• Angular, HTML, CSS, and JavaScript/TypeScript
• Unit testing using NUnit, Jasmine, and Karma
• IIS
• SQL Server, including functions, stored procedures, and scheduled jobs
• Experience with AI coding tools such as Claude, GitHub Copilot, or similar

Nice-to-Have Skills

• Integration testing
• Azure DevOps
• Power BI
• Cloud platforms such as Azure or AWS

Growth Opportunity

Over the next 1–2 years, you’ll have the opportunity to progress from handling customer-facing issues to owning complex technical problems and key product areas. You’ll build expertise across legacy and modern technologies, integrations, cloud, and AI, with a path toward leading technical initiatives, contributing to architectural and product decisions, mentoring engineers, and progressing toward a senior or technical leadership role.

Team Culture and Work Style

The Keyedin team is learning-focused, collaborative, and customer-focused. This role follows a hybrid work model with two days per week in the office and no shift work.

If this opportunity aligns with your experience and career goals, please share your updated resume and let me know a convenient time to connect.

The Role

We’re looking for a Senior Applied AI & Data Engineer to become our first dedicated AI and data engineer.

You’ll build conversational AI experiences across web, mobile, and in-store channels while developing the data foundation behind them. You’ll make key technical decisions and own your work through to production.

What You’ll Do

• Build AI assistants using tool calling to work with real product, search, and order systems

• Design guardrails and evaluation sets to ensure AI responses are accurate and safe

• Build real-time and voice-enabled AI experiences

• Improve product data quality through AI-assisted enrichment and review workflows

• Build data pipelines, analytics, and personalisation systems

• Work closely with web and mobile developers and help guide technical implementation

What You’ll Need

• 6+ years of experience building and running production backend systems

• Strong Python skills, plus experience with JavaScript/TypeScript backends

• Experience shipping at least one LLM-powered feature to real users

• Experience with search and relevance

• Experience building data pipelines and analytics stores

• Comfortable deploying and monitoring services on a major cloud platform

• Strong communication skills and the ability to work independently

Nice to Have

• Experience with speech or voice AI

• E-commerce or retail technology experience

• Experience building multilingual products

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.

About the role

We are building AI systems that read, understand and act on real business documents, bank statements, financial reports, policy documents and forms and putting them into production where accuracy and cost both matters.

This is not a research role and it is not a prompt-writing role. You will own features end to end: pick and deploy open-source models, build the pipelines around them, measure whether they actually work on our documents, drive the cost per document down, and keep the whole thing running in production.

You will work closely with the engineering and product teams, and your work will be directly used by business users from day one.

What you will do

Deploy and evaluate open-source models

• Select, deploy and benchmark open-source LLMs and vision-language models for specific, narrow use cases not general chat.
• Build evaluation sets from real documents and define what "good" means numerically (field-level accuracy, extraction recall, hallucination rate) before shipping.
• Run structured comparisons between models and approaches, and write up the trade-offs so the team can make a decision.
• Apply quantization, batching and other optimizations to fit models into a sensible GPU budget.

Build and optimize AI orchestration

• Design multi-step pipelines that combine deterministic code, ML models and LLM calls and know when not to use an LLM.
• Optimize for latency, cost and reliability: caching, batching, request routing, fallback tiers, retries and graceful degradation.
• Instrument pipelines so failures are visible and traceable rather than silent.

Ship to production

• Package models and services with Docker, expose them behind clean APIs, and deploy them to our GPU and CPU infrastructure.
• Handle the unglamorous production concerns: cold starts, timeouts, concurrency limits, versioning, rollback and monitoring.
• Own on-call-style responsibility for the AI features you build, including cost tracking.

Must-have skills

Programming & engineering

• Strong Python: type hints, async/await, dataclasses/Pydantic, clean module design, testing.
• REST API development with FastAPI (or Flask/Django with a willingness to move to FastAPI).
• Git, code review discipline, and the ability to write code someone else can maintain.
• Comfortable in Linux and on the command line.

Machine learning fundamentals

• Working knowledge of PyTorch and the Hugging Face ecosystem (transformers, tokenizers, accelerate).
• Understanding of inference-time concepts: tokenization, context windows, batching, precision (FP16/BF16/INT8), memory footprint.
• Ability to read a model card and a paper well enough to judge whether a model fits a use case.

Document processing

• Hands-on experience with at least two of: pypdfium2, PyMuPDF, pdfplumber, pdfminer.six, Docling, Unstructured, Surya, DocTR, LayoutLM family.
• Practical OCR experience (Tesseract, PaddleOCR, or a cloud OCR) and an understanding of when OCR is the wrong tool.
• Experience extracting tables from PDFs and dealing with merged cells, multi-line rows, and inconsistent column layouts.

Strongly preferred

You will be a much stronger candidate with any of these. We do not expect all of them.

Model serving & optimization

• vLLM, TGI, Ollama, llama.cpp, or Triton Inference Server.
• Quantization formats and tooling: GGUF, AWQ, GPTQ, bitsandbytes, ONNX Runtime, INT8 export.
• Serverless GPU platforms: Modal, RunPod, Replicate, Baseten including cold-start and container-lifecycle management.
• LoRA / QLoRA fine-tuning with PEFT for narrow, task-specific improvements.

Vision-language models

• Practical use of open VLMs: Qwen2.5-VL, InternVL, Granite Vision, Molmo, Phi-Vision, or similar.
• Awareness of where VLMs hallucinate especially on numeric and financial content and patterns for constraining them (using the model for layout only, sourcing values from the text layer, constrained decoding).

Orchestration & pipelines

• Workflow orchestration: Dagster, Airflow, Prefect, or Temporal.
• Async job patterns: Celery, RQ, or platform-native spawn/poll patterns.
• LLM orchestration frameworks (LangGraph, LlamaIndex, Haystack) with the judgement to know when plain Python is a better answer.
• Structured output enforcement: Instructor, Outlines, XGrammar, JSON schema / tool-use modes.

Evaluation & observability

• Building golden datasets and regression suites for extraction tasks.
• Eval tooling: promptfoo, DeepEval, Ragas, or in-house harnesses.
• LLM tracing and monitoring: Langfuse, Arize Phoenix, LangSmith, OpenTelemetry.

Nice extras

• Rule engines and policy evaluation (Open Policy Agent / Rego, Drools, rule-engine).
• Experience in fintech, lending, insurance or accounting documents.
• Handling of PII and data-security practices in document pipelines.
• Contributions to open-source ML or document-processing projects.

Why join us

• Real production ownership from month one your work goes to actual users, not a demo.
• Genuinely hard technical problems in document AI, not wrappers over an API.
• Small team, short decision cycles, direct access to leadership.
• Budget and freedom to evaluate and adopt new open-source models as they land.

To apply: send your CV along with a short note on one AI system you have taken to production what it did, what the accuracy was, and what broke.

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

Job Description: Senior Full Stack AI Engineer 

Position: Senior Full Stack AI Engineer ​

Experience: 6+ Years​

Location: Bangalore (preferred), Hyderabad​

Joining: Immediate 

About the Role 

We are looking for highly skilled Senior Full Stack AI Engineers who can independently 

design, build, and deploy AI-powered applications leveraging Large Language Models 

(LLMs). The ideal candidate should be equally comfortable working across the full stack, 

from developing scalable backend services and modern frontend applications to creating AI-

driven solutions and automated testing frameworks that enable developer-led quality 

engineering. 

This role requires hands-on expertise in LLM development, application architecture, and test 

automation, effectively helping organizations accelerate delivery while reducing dependency 

on traditional QA teams. 

Key Responsibilities 

∙Design, develop, and deploy AI-powered applications using Large Language Models 

(LLMs), with experience in Claude preferred. 

∙Architect and build scalable full stack applications using Java, Spring Boot, 

ReactJS, NextJS, TypeScript, and JavaScript. 

∙Develop intelligent workflows utilizing AI agents, prompt engineering, retrieval-

augmented generation (RAG), and model integrations. 

∙Create end-to-end automated test suites using Playwright, Perfecto, and other 

modern automation frameworks to support developer-led testing. 

∙Build and integrate RESTful APIs and microservices following modern architecture 

principles. 

∙Design and manage data solutions using SQL, NoSQL, and MongoDB. 

∙Develop event-driven applications using messaging platforms such as Kafka. 

∙Implement secure, scalable, and high-performance solutions using Spring Security, 

OAuth, and multi-threaded programming. 

∙Leverage AWS services including ECS, Lambda, and Step Functions to build cloud-

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.