AI Engineer with LLM

Recex.co; Bengaluru; On-site; INR 1,500,000 - 2,200,000; Full time

Job summary

A leading AI solutions company is seeking an AI Engineer specialized in Large Language Models (LLMs) to design and develop innovative applications. The ideal candidate will have 5-7 years of software development experience, including expertise in LLMs and strong skills in Python. This full-time role offers the chance to work collaboratively in cross-functional teams and contribute significantly to exciting AI projects.

Qualifications

• 5-7 years of software development experience with 3+ years in AI.
• Expert proficiency in Python and its relevant ecosystem.
• Deep understanding of Transformer architectures and LLM internals.

Responsibilities

• Design and optimize applications using Large Language Models.
• Lead fine-tuning and evaluation of LLMs.
• Collaborate with cross-functional teams to implement AI solutions.

Skills

Python

LLM expertise

NLP knowledge

Critical thinking

Communication skills

Education

Bachelor's or master's degree in computer science or related field

Tools

Hugging Face Transformers

Langchain

LangGraph

AWS

Job description

Position: AI Engineer with LLM at Recex.co

Overview

We are seeking a highly skilled AI Engineer specialized in Large Language Models (LLMs) to design, develop, and deploy innovative AI-powered applications and intelligent agents. The candidate will contribute from ideation and research through to robust and scalable production deployment.

Key Responsibilities

• LLM Application & Agent Development: Design, build, and optimize sophisticated applications, intelligent AI agents, and systems powered by Large Language Models.
• Advanced Prompt Engineering & Optimization: Develop, test, iterate, and refine prompt engineering techniques to elicit desired behaviours, ensure reliability, and maximize performance from LLMs for complex tasks.
• LLM Fine-Tuning & Customization: Lead fine-tuning of pre-trained LLMs on domain-specific datasets to enhance capabilities and align with business needs.
• LLM Evaluation & Benchmarking: Establish evaluation frameworks, metrics, and processes to assess LLM performance, accuracy, fairness, safety, and robustness.
• Framework Utilization (Langchain/LangGraph): Architect and develop LLM-driven workflows, chains, multi-agent systems, and graphs using Langchain and LangGraph.
• Cross-Functional Collaboration: Work with Principal Architects, data scientists, software engineers, and product teams to integrate LLM-based solutions into products and services.
• Performance, Scalability & Cost Optimization: Optimize LLM inference speed, throughput, scalability, and cost-effectiveness for production environments.
• Stay Current with LLM Advancements: Research and experiment with latest LLM architectures, open-source models, prompt engineering, agent patterns, fine-tuning methods, and ethical AI considerations.
• LLMOps & Governance: Contribute to LLMOps infrastructure, including model versioning, monitoring, feedback loops, data management for fine-tuning, and governance for deployments.
• API & Service Development: Develop robust APIs and microservices to serve LLM-based applications and agents reliably and at scale.
• Documentation & Knowledge Sharing: Create comprehensive technical documentation and share best practices with technical and non-technical stakeholders.

Required Qualifications

• Educational Background: Bachelor's or master's degree in computer science, artificial intelligence, machine learning, computational linguistics, or related field.
• Professional Experience: 5-7 years of software development experience, with a minimum of 3+ years in AI development, including hands-on experience with LLMs, agent development, and related technologies.
• Programming Proficiency: Expert in Python and its ecosystem relevant to AI/LLMs.
• LLM, NLP & Agent Expertise: Deep understanding of NLP concepts, Transformer architectures, LLM internals, and AI agent design.
• LLM Frameworks & Tools: Experience with Hugging Face Transformers, Langchain, LangGraph, LlamaIndex, and similar tools.
• Cloud Platform Experience: Experience with AWS, GCP, or Azure and their AI/ML services for deploying LLMs (e.g., Bedrock, Vertex AI, OpenAI Service).
• Fine-Tuning & Evaluation Experience: Experience in fine-tuning LLMs and evaluating model and agent performance.
• MLOps/LLMOps Practices: Familiarity with MLOps principles for LLM lifecycles (experiment tracking, model registries, CI/CD for LLMs).
• Data Handling for LLMs: Understanding of data preprocessing, augmentation, and management for training and fine-tuning LLMs.
• Version Control: Proficiency with Git and collaborative workflows.

Preferred Qualifications

• Advanced LLM Architectures & Prompt Engineering: Mastery of diverse architectures and prompt engineering techniques.
• Autonomous Agent & Multi-Agent Systems: Experience designing and deploying autonomous AI agents or multi-agent systems.
• Vector Databases: Familiarity with Pinecone, Weaviate, Milvus, Chroma for RAG and semantic search.
• Distributed Systems for LLMs: Knowledge of distributed training and inference for very large models.
• Ethical AI & Responsible LLM/Agent Development: Understanding of bias, safety, and responsible AI practices.
• Research & Publications: Contributions to LLM or AI agent research or active participation in open-source projects.
• Domain-Specific LLM/Agent Applications: Experience applying LLMs to specific industry domains.
• Cloud Certifications: Relevant cloud certifications (e.g., AWS, Google, Azure) or similar credentials.

Technical Skillset

• Programming: Python (expert), SQL.
• LLM/NLP/Agent Frameworks: Transformers, Langchain, LangGraph, LlamaIndex, PyTorch, TensorFlow, and related tools.
• Cloud Platforms & LLM Services: AWS SageMaker/Bedrock, Google Vertex AI, Azure ML.
• Tools: Docker, Kubernetes, MLflow, Weights & Biases, Vector Databases.
• Databases: SQL and NoSQL databases; Vector Databases.

Soft Skills

• Analytical, creative, and critical thinking with problem-solving in generative AI and intelligent agents.
• Excellent communication to explain complex LLM concepts to diverse audiences.
• Ability to work independently and in cross-functional teams.
• Attention to data quality, model behavior, agent reliability, and system robustness.
• Curiosity and adaptability in the rapidly evolving field of LLMs and AI agents.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Engineering and Information Technology

Industries

• Human Resources Services

Note: this description retains the core requirements and responsibilities for the AI Engineer with LLM role at Recex.co. It omits extraneous boilerplate where possible while preserving the essential qualifications and expectations.