Pragma Edge – AI Developer Trainee (Fresher)

Job Description

Pragma Edge is hiring AI Developer Trainees in Hyderabad for an opportunity focused on Artificial Intelligence, Agentic AI, Natural Language Processing and Large Language Models (LLMs). The position is designed for candidates with 0 to 2 years of experience, with hands-on exposure to Agentic AI or LLM technologies being preferred. Selected professionals will work on the design, development and deployment of intelligent systems that use modern AI technologies to address real-world business problems. The role provides exposure to multi-agent architectures, autonomous AI agents, LLM integration, NLP applications and AI-powered workflows. As an AI Developer Trainee, you will work with technologies and frameworks such as CrewAI, LangGraph, AutoGen and LangChain while learning how intelligent agents can coordinate tasks, use external tools and APIs, maintain contextual memory and execute multi-step workflows.

A major part of the role involves developing and improving AI models and applications. Trainees will work with pre-trained large language models and contribute to activities such as model adaptation, prompt engineering, fine-tuning and NLP solution development. Applications may involve summarization, text classification, text generation and other language-based use cases. The position also requires strong Python programming skills and exposure to machine learning frameworks such as PyTorch or TensorFlow. Candidates will work with data as well, including preprocessing and analysing large-scale datasets and collaborating with data engineering teams on scalable data pipelines. Understanding how data is prepared, processed and supplied to AI systems is important because the quality and scalability of the underlying data can directly influence the performance of AI applications.

The role also includes AI evaluation, optimisation, documentation and research integration. Trainees will help implement evaluation metrics and work toward improving model performance, latency and scalability. They may collaborate with research, product and engineering teams to translate emerging AI techniques into practical solutions. The position encourages professionals to stay informed about developments in LLMs, Agentic AI, multi-agent architectures and AI safety. Knowledge of RAG, vector databases, cloud platforms and open-source AI projects can provide additional value. Because the role involves communicating technical findings, successful candidates should be able to document model behaviour and agent workflows and explain relevant concepts to both technical and non-technical stakeholders. The position offers an opportunity for freshers to build practical experience in one of the rapidly developing areas of modern AI engineering.

Roles & Responsibilities

1. Develop Agentic AI Systems
   Design and implement intelligent agent architectures that can understand tasks, make decisions, use tools and execute multi-step workflows.
2. Build Multi-Agent Workflows
   Create workflows where multiple specialised AI agents can coordinate tasks, exchange information and contribute to broader problem-solving objectives.
3. Work with AI Frameworks
   Use frameworks such as CrewAI, LangGraph, AutoGen and LangChain or similar technologies to develop agent-based AI applications.
4. Integrate LLMs with Tools
   Connect large language models with APIs, external tools, data sources and memory systems to create more capable AI-powered applications.
5. Develop NLP Solutions
   Build solutions for use cases such as text summarisation, classification, generation and other Natural Language Processing applications.
6. Fine-Tune AI Models
   Work with pre-trained language models and contribute to model adaptation, fine-tuning and prompt engineering activities based on project requirements.
7. Process Large Datasets
   Preprocess, analyse and prepare large-scale datasets for AI and machine learning applications while maintaining appropriate data quality.
8. Support Data Engineering
   Collaborate with data engineering teams to understand and contribute to scalable data pipelines required for AI systems.
9. Evaluate Model Performance
   Implement relevant evaluation metrics and analyse AI model outputs to identify opportunities for improving accuracy, reliability and effectiveness.
10. Optimise AI Applications
    Work on improving model performance, response latency, scalability and overall efficiency for production-oriented AI applications.
11. Collaborate Across Teams
    Work with research, product and engineering professionals to transform AI concepts and emerging technologies into practical solutions.
12. Document AI Workflows
    Maintain technical documentation covering models, prompts, agent architectures, workflows, experiments and implementation decisions.
13. Research Emerging AI Technologies
    Stay informed about developments in LLMs, Agentic AI, multi-agent systems, AI safety and related technologies and assess their practical relevance.
14. Present Technical Findings
    Communicate project results, experiments and technical findings to both technical and non-technical stakeholders in a clear and structured manner.

Requirements & Eligibility

1. Educational Qualification
   Candidates should have a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science or a closely related technical discipline.
2. Experience Level
   The position is advertised for candidates with 0–2 years of experience, making it relevant to freshers and early-career AI professionals.
3. Strong Python Skills
   Candidates should have strong programming knowledge in Python and be comfortable developing scripts, data-processing workflows and AI/ML applications.
4. Machine Learning Frameworks
   Experience with PyTorch or TensorFlow is required, along with an understanding of how machine learning models are developed, trained or evaluated.
5. LLM Knowledge
   Candidates should have hands-on exposure to Large Language Models, prompt engineering and fine-tuning and understand the fundamentals of modern generative AI applications.
6. Agentic AI Exposure
   Familiarity with Agentic AI, autonomous agents or multi-agent systems is important for this role. Academic projects, personal projects or professional experience can demonstrate relevant exposure.
7. Distributed Systems & Data Processing
   Candidates should understand distributed systems and large-scale data processing concepts, particularly when working with AI applications that require substantial amounts of data.
8. Problem-Solving Skills
   Strong analytical and problem-solving abilities are required to investigate model behaviour, troubleshoot AI workflows and develop practical solutions.
9. Collaboration Skills
   Candidates should be comfortable working with research, product, engineering and data teams and communicating technical ideas effectively.
10. RAG & Vector Databases
    Experience with Retrieval-Augmented Generation (RAG) and vector databases is a preferred skill that can strengthen an applicant's profile.
11. Cloud Technology Exposure
    Familiarity with cloud platforms such as IBM Cloud, AWS, Google Cloud Platform or Microsoft Azure is considered an advantage.
12. AI Safety Awareness
    An understanding of AI safety, alignment and ethical AI principles is desirable, particularly for candidates working on autonomous and generative AI systems.
13. Open-Source Experience
    Contributions to open-source projects, AI repositories or relevant technical communities are considered a valuable additional qualification.
14. Additional AI Frameworks
    Familiarity with WatsonX, LangChain, AutoGen or LangGraph can provide additional preparation for the role.

Expected Salary

The supplied Pragma Edge job posting does not specify a salary range for the AI Developer Trainee position. For an AI/ML Developer Trainee or entry-level AI Engineer with 0–2 years of experience in Hyderabad, a reasonable market-oriented estimate is approximately ₹3.5 lakh to ₹7 lakh per annum, with actual compensation depending on technical skills, practical AI project experience, educational background and the company's compensation structure.

Candidates with demonstrable experience in LLMs, Agentic AI, Python, RAG, vector databases and cloud platforms may encounter different compensation levels depending on the specific responsibilities and hiring requirements.

Key Technologies & Skills

The Pragma Edge AI Developer Trainee position covers a broad modern AI technology stack. Candidates preparing for the opportunity should pay particular attention to Python, LLMs, prompt engineering, fine-tuning, NLP and Agentic AI.

For agent development, learning frameworks such as LangChain, LangGraph, AutoGen and CrewAI can help candidates understand how autonomous and multi-agent workflows are structured. Candidates should also understand how LLMs interact with external tools, APIs, memory systems and data sources.

Machine learning fundamentals remain important as well. Familiarity with PyTorch or TensorFlow, model evaluation, data preprocessing and large-scale data processing can provide the technical foundation needed for AI development. Candidates interested in production-oriented AI should additionally explore RAG, embeddings, vector databases, cloud deployment and AI evaluation techniques.

Career Growth Opportunities

An AI Developer Trainee position can provide a foundation for several career paths within the rapidly developing artificial intelligence ecosystem. As professionals gain practical experience, they can progress toward roles such as AI Engineer, Machine Learning Engineer, Generative AI Engineer, LLM Engineer, NLP Engineer, AI Application Developer or Agentic AI Engineer.

Professionals can also specialise in areas such as AI agents, RAG systems, model evaluation, NLP, machine learning infrastructure, AI platforms or cloud-based AI applications. Building a portfolio of practical projects involving LLMs, agents, vector databases and AI automation can further strengthen an early-career professional's technical profile.

About Pragma Edge

Pragma Edge operates in the IT Services sector and provides technology-focused solutions for organisations. The company works with modern technologies to support business and technology requirements and provides opportunities for professionals to work on emerging technical areas.

The AI Developer Trainee opportunity reflects a focus on modern artificial intelligence technologies, including large language models, Agentic AI, Natural Language Processing, multi-agent architectures and AI application development. For early-career professionals, this environment can provide practical exposure to the development lifecycle of AI-powered systems.

Work Schedule

The advertised position is based in Hyderabad, India, and the listed shift timing is 2:00 PM to 11:00 PM IST. The requirement is described as immediate, and the posting indicates that there are four positions available.

Candidates should therefore be comfortable working the specified shift and should be prepared to collaborate with teams operating within the defined working schedule.

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