AI/ML Engineer

Sr Engineer – Artificial Intelligence

Job Summary 

As an AI Engineer at Emerson, you will be responsible for analysing complex data sets to

identify trends, develop predictive models, and provide actionable insights. You will work closely

with cross-functional teams to understand business needs and deliver data-driven solutions that

enhance decision-making and drive business growth.

 In This Role, Your Responsibilities Will Be:

 Analyze large, complex data sets using statistical methods and machine learning

techniques to extract meaningful insights.

 Develop and implement predictive models and algorithms to solve business problems

and improve processes.

 Create visualizations and dashboards to effectively communicate findings and insights to

stakeholders.

 Work with data engineers, product managers, and other team members to understand

business requirements and deliver solutions.

 Clean and preprocess data to ensure accuracy and completeness for analysis.

 Prepare and present reports on data analysis, model performance, and key metrics to

stakeholders and management.

 Participate in regular Scrum events such as Sprint Planning, Sprint Review, and Sprint

Retrospective

 Stay updated with the latest industry trends and advancements in data science and

machine learning techniques.

For This Role, You Will Need:

 Bachelor’s degree in computer science, Data Science, Statistics, or a related field or a

master's degree or higher is preferred.

 Total 5-7 years of industry experience

 More than 3 years of experience in a data science or analytics role, with a strong track

record of building and deploying models.

 Proficiency in programming languages such as Python or R, and experience with data

manipulation libraries (e.g., pandas, NumPy).

 Excellent understanding of Agentic Frameworks like Microsoft Agent Framework.

 Experience with NLP, NLG, and Large Language Models Open Source as well as Cloud

based models.

 Experience with SQL and NoSQL databases such as MongoDB, Cassandra, Vector

databases

 Experience with Dockers, Asynchronous Data Orchestrators, environments etc.

 Strong analytical and problem-solving skills, with the ability to work with complex data

sets and extract actionable insights.

 Excellent verbal and written communication skills, with the ability to present complex

technical information to non-technical stakeholders.

Preferred Qualifications that Set You Apart:

 Prior experience in engineering domain would be nice to have

 Prior experience in working with teams in Scaled Agile Framework (SAFe) is nice to

have

 Possession of relevant certification/s in data science from reputed universities

specializing in AI.

 Familiarity with cloud platforms, Microsoft Azure is preferred

 Ability to work in a fast-paced environment and manage multiple projects simultaneously.

 Strong analytical and troubleshooting skills, with the ability to resolve issues related to

model performance and infrastructure.

About Nexora Group

Nexora Group is a technology and innovation-driven organization dedicated to building intelligent solutions that leverage Artificial Intelligence, Machine Learning, Data Analytics, and emerging technologies. We are committed to fostering talent by providing aspiring professionals with practical exposure, mentorship, and opportunities to work on real-world projects.

Internship Overview

Nexora Group is looking for enthusiastic and driven AI/ML Interns to join our team. This internship is ideal for students and recent graduates who are passionate about Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI. Interns will gain hands-on experience working on real-world AI projects, developing intelligent models, and solving complex business challenges using data-driven approaches.

Key Responsibilities

• Assist in developing, training, and evaluating Machine Learning models.
• Collect, clean, and preprocess datasets for AI/ML applications.
• Conduct exploratory data analysis and feature engineering.
• Work on Deep Learning, Natural Language Processing (NLP), and Computer Vision projects.
• Research and implement AI algorithms and emerging technologies.
• Support the development of Generative AI and Large Language Model (LLM)-based solutions.
• Optimize model performance and evaluate results using industry-standard metrics.
• Document project workflows, findings, and technical reports.
• Collaborate with cross-functional teams to develop innovative AI solutions.

Required Skills

• Basic understanding of Machine Learning and Artificial Intelligence concepts.
• Knowledge of Python programming.
• Familiarity with libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, or Keras.
• Understanding of data structures, algorithms, and statistics.
• Basic knowledge of Deep Learning, NLP, or Computer Vision concepts.
• Strong analytical and problem-solving skills.
• Good communication and teamwork abilities.
• Willingness to learn and adapt to new technologies.

Preferred Qualifications

• Experience with AI/ML projects, hackathons, or research work.
• Knowledge of Generative AI, Prompt Engineering, and LLMs.
• Familiarity with cloud platforms and AI deployment tools.
• Certifications in AI, Machine Learning, or Data Science are a plus.
• GitHub projects or portfolio showcasing AI/ML work.

Eligibility

• Undergraduate or postgraduate students pursuing Computer Science, Artificial Intelligence, Machine Learning, Data Science, Information Technology, or related fields.
• Recent graduates seeking practical industry experience.
• Candidates with a strong interest in AI innovation and research.

What You'll Gain

• Hands-on experience with real-world AI and Machine Learning projects.
• Mentorship from experienced AI professionals.
• Exposure to cutting-edge AI tools, frameworks, and technologies.
• Internship Completion Certificate.
• Letter of Recommendation based on performance.
• Opportunity for a Pre-Placement Offer (PPO) for outstanding performers.
• Professional networking and career development opportunities.

Job Description:

We are seeking a highly skilled Machine Learning Engineer to join our team. The ideal candidate will have a strong background in Natural Language Processing (NLP), Large Language Models (LLMs), and Python programming.

You will work closely with data scientists, product managers, and data engineers to design, develop, and deploy high-performance AI/ML models and integrate generative AI solutions into existing workflows.

Your responsibilities will include:

• Collaborating with cross-functional teams to design and deliver high-performance AI models, including NLP, computer vision, semantics engines, linguistic analysis, risk management, and time-series prediction models. Integrating generative AI solutions into existing workflow systems.
• Developing and maintaining the ML Operations CI/CD pipeline for seamless deployment and monitoring. Training, tuning, and optimizing AI models and algorithms for enhanced performance.
• Implementing complex real-time data and AI/ML applications to capture knowledge and automate decision-making processes.
• Creating ML/AI models for business teams and establishing metrics to track their accuracy and performance. Overseeing the full lifecycle of algorithm development, from ideation to deployment and monitoring. Evaluating and ranking ML algorithms based on their potential success in solving specific problems.
• Serving as an internal resource for AI/ML needs, providing guidance and insights to stakeholders during strategic discussions.

Required Experience and Skills:

Machine Learning:

• Proficient in generative AI techniques, prompt engineering, and Retrieval-Augmented Generation (RAG) (3+ years).
• Experience with Large Language Models (LLMs) such as OpenAI, Gemini, LLAMA, and other state-of-the-art models (3+ years).
• Expertise in using ML/AI libraries such as Pandas, NumPy, PyTorch, TensorFlow, Keras, BERT, LayoutLM, and traditional ML algorithms (5+ years).
• Experience with distributed ML/AI training libraries/models: Koalas, Horovod, DDP.

Python Programming and Software Engineering:

• Expertise in Pythonic clean coding practices, including the use of decorators, generators, and descriptors (5+ years).
• Strong understanding of software design principles such as DRY, OAOO, YAGNI, KIS, EAFP/LBYL, and defensive programming (2+ years).
• Proficient in software design concepts focusing on cohesion and coupling (2+ years). Knowledge of SOLID principles (2+ years).

Education and Experience:

• Minimum Bachelor's degree or foreign equivalent in Computer Science, Electrical Engineering, or a closely related field.
• At least 5 years of experience as a software engineer and 5 years of ML-related programming.

About the Role:

We are looking for an ideal candidate with 5+ years of experience in Data Science / Machine Learning, with strong hands-on experience in Generative AI, Large Language Models (LLMs), NLP, and AI-powered applications. The candidate should be comfortable working across the complete AI lifecycle—from understanding business requirements and experimenting with models to building, evaluating, deploying, and monitoring production-grade GenAI solutions.

The role requires a combination of strong technical expertise, business understanding, problem-solving ability, and stakeholder management skills.

Key Responsibilities:

Generative AI & LLM

·      Design, develop, and deploy Generative AI and LLM-based solutions for enterprise use cases.

·      Work with models such as OpenAI, Azure OpenAI, Llama, Mistral, Gemini, or equivalent LLM platforms.

·      Develop applications using prompt engineering, structured outputs, function/tool calling, and LLM orchestration.

·      Design and implement Retrieval-Augmented Generation (RAG) solutions.

·      Work with vector databases and semantic search for enterprise knowledge retrieval.

·      Develop and evaluate AI agents and multi-step AI workflows.

·      Implement techniques such as prompt optimization, context management, grounding, and hallucination reduction.

·      Develop AI solutions for text classification, summarization, information extraction, question answering, document intelligence, and other enterprise use cases.

Machine Learning & Data Science

·      Develop and optimize traditional Machine Learning and statistical models where appropriate.

·      Perform data exploration, feature engineering, model selection, training, validation, and evaluation.

·      Apply appropriate ML and statistical techniques to solve business problems.

·      Work with structured, unstructured, and semi-structured data.

·      Develop scalable data pipelines to support AI/ML solutions.

·      Collaborate with Data Engineers to prepare and manage data for AI applications.

AI Evaluation & Productionization

·      Design evaluation frameworks to measure LLM accuracy, relevance, groundedness, toxicity, latency, and cost.

·      Implement guardrails and responsible AI practices.

·      Monitor model and application performance in production.

·      Identify model/data drift and implement appropriate improvement strategies.

·      Optimize AI solutions for performance, scalability, reliability, and cost.

·      Support deployment and productionization of AI/ML solutions.

·      Client & Delivery Responsibilities

·      Work closely with the CEO, Delivery team, Solution Architects, Engineering teams, and clients to understand business problems and identify AI opportunities.

·      Translate business requirements into practical AI/ML solutions.

·      Participate in client discussions, solution presentations, technical workshops, and POCs.

·      Develop rapid prototypes and demonstrate the feasibility of GenAI solutions.

·      Convert successful POCs into scalable, production-ready applications.

·      Provide technical guidance and contribute to AI solution architecture.

·      Prepare technical documentation, solution approaches, and project estimates where required.

·      Stay current with developments in Generative AI, LLMs, Agentic AI, and AI engineering.

Required Skills:

·       5+ years of hands-on experience in Data Science, Machine Learning, AI, or a related field.

·      Strong practical experience in Generative AI and LLM-based applications.

·      Strong proficiency in Python.

·      Strong understanding of Machine Learning and statistical concepts.

·      Hands-on experience with:

o       LLMs

o       Prompt Engineering

o       RAG

o       Vector Databases

o       Embeddings

o       Semantic Search

o       LLM Evaluation

o       AI Guardrails

·      Experience with frameworks/tools such as LangChain, LangGraph, LlamaIndex, or equivalent.

·      Experience with APIs and integrating LLMs into enterprise applications.

·      Strong SQL and data handling skills.

·      Experience working with large and complex datasets.

·      Strong understanding of NLP concepts.XX

Technical Skills:

·      Experience with OpenAI / Azure OpenAI / AWS Bedrock / Google Vertex AI.

·      Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, or equivalent.

·      Experience with Databricks, Snowflake, or cloud data platforms.

·      Experience with Docker and CI/CD.

·      Exposure to AWS, Azure, or GCP.

·      Experience with ML/AI deployment and MLOps.

·       Knowledge of AI security, data privacy, governance, and responsible AI.

·      Experience building AI Agents / Agentic AI workflows.

·      Experience with multimodal AI is an added advantage

Key Competencies

·      Strong analytical and problem-solving ability.

·      Ability to translate business problems into practical AI solutions.

·      Strong communication and presentation skills.

·      Ability to interact confidently with senior stakeholders and clients.

·      Strong ownership and delivery mindset.

·      Ability to work independently in a fast-paced environment.

• Strong experimentation and innovation mindset.
• Ability to balance technical feasibility, business value, scalability, and cost.

Required Education & Experience:

·      Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related discipline

About the Job :

We are looking for a passionate and driven AI Intern to join our dynamic team. As an intern, you will have the opportunity to work on real-world projects, develop AI models, and collaborate with experienced professionals in the field. This internship is designed to provide hands-on experience in AI and machine learning, offering you the chance to contribute to impactful projects while enhancing your skills.

Job Description:

We are seeking a talented Artificial Intelligence Specialist to join our dynamic team. As an AI Specialist, you will be responsible for developing, implementing, and optimizing AI models and algorithms. You will collaborate closely with cross-functional teams to integrate AI capabilities into our products and services. The ideal candidate should have a strong background in machine learning, deep learning, and natural language processing, with a passion for applying AI to real-world problems.

Responsibilities:

• Design, develop, and deploy AI models and algorithms.
• Conduct data analysis and pre-processing to prepare data for modeling.
• Implement and optimize machine learning algorithms.
• Collaborate with software engineers to integrate AI models into production systems.
• Evaluate and improve the performance of existing AI models.
• Stay updated with the latest advancements in AI research and apply them to enhance our products.
• Provide technical guidance and mentorship to junior team members.

Requirements:

• Any Graduate / Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field; Master's degree preferred.
• Proven experience in developing and implementing machine learning models and algorithms.
• Strong programming skills in languages such as Python, R, or Java.

Benefits :

• Internship Certificate
• Letter of Recommendation
• Performance-Based Stipend
• Part-time work from home (2-3 hours per day)
• 5 days a week, fully flexible shift

Role Overview 

As a Data Scientist, you will work with business stakeholders, AI engineers, and domain experts to transform data into actionable insights and intelligent solutions. You will develop machine learning models, perform statistical analysis, and contribute to AI-driven products that create measurable business impact. 

Key Responsibilities 

Data Science & Machine Learning 

• Analyze structured and unstructured data to identify patterns, trends, and business opportunities.  
• Perform exploratory data analysis (EDA), feature engineering, and data preparation.  
• Develop, evaluate, and optimize machine learning models for prediction, classification, clustering, and forecasting.  
• Apply statistical techniques to solve business problems and validate model performance.  
• Design and execute experiments to improve model accuracy and business outcomes.  

 AI Solution Development 

• Collaborate with AI Engineers, Data Engineers, and domain experts to build AI-powered solutions.  
• Translate business requirements into scalable data science approaches.  
• Contribute to Generative AI and advanced analytics initiatives where applicable.  
• Document methodologies, model performance, and key findings.  

 Required Technical Skills 

• Strong programming skills in Python and SQL for data analysis, feature engineering, and machine learning.  
• Strong understanding of Statistics, Probability, Linear Algebra, and Calculus as applied to machine learning and data science.  
• Experience with Exploratory Data Analysis (EDA), data preprocessing, feature engineering, feature selection, and handling missing or imbalanced data.  
• Good understanding of Supervised, Unsupervised, and Ensemble Machine Learning algorithms, including their assumptions, strengths, limitations, and appropriate use cases.  
• Strong knowledge of Regression, Classification, Clustering, Time Series Forecasting, Dimensionality Reduction, Recommendation Systems, and Anomaly Detection techniques.  
• Experience with Model Evaluation, Cross-Validation, Hyperparameter Optimization, Bias-Variance Trade-off, Feature Importance, Explainable AI (XAI), and Performance Metrics.  
• Understanding of Statistical Inference, Hypothesis Testing, Probability Distributions, Sampling Techniques, Confidence Intervals, and A/B Testing.  
• Experience translating business problems into analytical approaches and developing scalable, data-driven solutions.  
• Working knowledge of Generative AI, Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG) is preferred. 

Preferred Qualifications 

• Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related field.  
• 2–4 years of experience developing machine learning or data science solutions.  
• Experience working on end-to-end data science projects in a business environment.  

 Nice to Have 

• Exposure to Generative AI, LLMs, RAG, or Agentic AI.  
• Experience with Computer Vision or Natural Language Processing (NLP).  
• Familiarity with cloud-based AI platforms.  
• Knowledge of construction, engineering, manufacturing, or industrial domains.  
• Participation in hackathons, research, Kaggle competitions, or open-source projects.  

 Soft Skills 

Strong analytical and problem-solving skills, effective communication and collaboration, ownership mindset, adaptability, continuous learning, and a passion for innovation.

About E2M:

E2M Solutions works as a trusted white-label partner for digital agencies. We support agencies with consistent and reliable delivery through services such as website design, web development, eCommerce, SEO, AI SEO, PPC, AI automation, and content writing .Founded on strong business ethics, we are an equal opportunity organization powered by 300+ experienced professionals, partnering with 400+ digital agencies across the US, UK, Canada, Europe, and Australia. At E2M, we value ownership, consistency, and people who are committed to doing meaningful work and growing together .If you’re someone who dreams big and has the gumption to make them come true, E2M has a place for you.

Role Overview:

We are seeking a highly skilled and client-centric AI Consultant/AI Adoption Specialist to join our growing team. In this pivotal role, you'll serve as a vital link between our clients' strategic objectives and the transformative power of AI. You'll primarily focus on understanding their needs, scoping opportunities, and architecting actionable AI roadmaps.

Key Responsibilities:

• Collaborate closely with clients to understand their challenges and identify opportunities to apply AI.
• Assess client requirements and prepare solution strategies using AI tools and methodologies.
• Work with internal teams to design, propose, and help execute AI-powered solutions.
• Provide AI-based recommendations that align with the client’s business objectives.
• Communicate technical possibilities in a business-friendly manner to decision-makers.
• Take ownership of the client journey from discovery to implementation and support.
• Stay updated with AI trends, tools, and real-world use cases that can benefit clients.

Required Skills & Qualifications:

• Minimum 2+ Years of hands on experience into Custom AI Development.
• Minimum 3+ years of experience in roles like Project Manager, Customer Success Manager, or Account Manager, preferably in a service-based company or digital agency.
• Strong understanding of AI concepts, trends, and tools (e.g., NLP, ML, Chatbots, Automation, native cloud technologies).
•  Some hands-on experience in AI projects – either through execution, coordination, or implementation.
• Ability to manage multiple client engagements and communicate effectively with both technical and non-technical stakeholders.
•  Strong problem-solving mind set with the ability to translate business needs into AI opportunities.
• Flexible to work with international clients, especially in the US time zone as needed.

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. 

About the Internship

Nexora Group is looking for passionate and innovative students interested in Artificial Intelligence (AI) and Machine Learning (ML). This internship offers an opportunity to work on real-world AI projects, explore machine learning techniques, and gain hands-on experience with emerging technologies that are transforming industries worldwide.

Interns will collaborate with mentors, work on practical assignments, and develop industry-relevant skills in AI, ML, data-driven decision-making, and intelligent systems.

Key Responsibilities

• Assist in developing and testing Machine Learning models.
• Work on AI-based applications and automation projects.
• Analyze datasets and prepare data for model training.
• Research emerging AI and Machine Learning technologies.
• Evaluate model performance and improve accuracy.
• Create reports and documentation for assigned projects.
• Participate in project discussions, training sessions, and team meetings.
• Support the development of innovative AI-driven solutions.

Required Skills

• Basic knowledge of Python programming.
• Understanding of Artificial Intelligence and Machine Learning concepts.
• Familiarity with data analysis and statistics.
• Knowledge of Machine Learning libraries such as Scikit-learn, TensorFlow, or PyTorch is a plus.
• Strong analytical and problem-solving skills.
• Ability to learn new technologies quickly.
• Good communication and teamwork skills.

Eligibility

• B.Tech, M.Tech, BCA, MCA, B.Sc., M.Sc., or related disciplines.
• Students pursuing Computer Science, Artificial Intelligence, Data Science, Information Technology, Mathematics, or related fields.
• Freshers and recent graduates are encouraged to apply.

What You Will Learn

✅ Artificial Intelligence Fundamentals

✅ Machine Learning Algorithms

✅ Data Preprocessing & Model Training

✅ Generative AI Concepts

✅ Predictive Analytics

✅ AI Project Development

✅ Industry-Oriented Problem Solving

Benefits

✅ Internship Completion Certificate

✅ Letter of Recommendation (Performance-Based)

✅ Hands-on AI & ML Project Experience

✅ Professional Mentorship & Guidance

✅ Resume & LinkedIn Profile Enhancement

✅ Portfolio Development Support

✅ Exposure to Real-World AI Applications

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.