Join i2e Consulting as an Applied AI Engineer in our AI Labs team!

If you are someone who builds with AI-native tools, ships fast, and brings deep expertise in production-grade agentic workflows and AI-powered applications this opportunity is for you. Enroll today to participate in our innovation sprint!

Location : Remote

Work Timings : 1pm to 10pm

- Selected profiles will be invited for an in-person interview in March in Bangalore/Mumbai.

Job Title : Applied AI Engineer - AI Labs

About the Role :

AI Labs is responsible for building and deploying next-generation AI-powered solutions across the organization and for our clients. Our focus is on creating production-grade systems using Large Language Models (LLMs), intelligent agents, and retrieval-based architectures that automate workflows, enhance decision-making, and accelerate delivery across the enterprise.

This role is hands-on and delivery-focused. The Applied AI Engineer will work on building, integrating, and scaling real-world AI systems rather than on model research or algorithm development.

Key Responsibilities :

- Design, develop, and deploy AI-driven solutions using Large Language Models (LLMs) and related technologies.

- Build and maintain Retrieval-Augmented Generation (RAG) pipelines, agent-based workflows, and AI orchestration layers.

- Integrate LLM-powered capabilities into enterprise applications, internal tools, and client-facing platforms.

- Develop prompt frameworks, tool-calling logic, and guardrails to ensure reliable, safe, and high-quality AI outputs.

- Implement evaluation, monitoring, and feedback mechanisms to continuously improve accuracy, cost efficiency, and system performance.

- Work closely with business stakeholders, product teams, and engineering teams to translate requirements into scalable AI solutions.

- Document architectures, workflows, and implementation patterns to support maintainability and knowledge sharing.

Required Skills & Experience :

Core Technical Skills :

- Strong proficiency in Python and experience building API-driven applications.

- Hands-on experience working with Large Language Model platforms (e.g., OpenAI, Anthropic, Groq, or similar).

- Experience with prompt engineering, structured outputs (JSON, tool calling), and multi-step LLM workflows.

- Experience with vector databases and embedding-based retrieval systems (e.g., FAISS, Pinecone, Weaviate, Chroma).

- Familiarity with integrating AI systems with databases, APIs, and enterprise software.

AI Systems & Architecture :

- Experience building or working with RAG pipelines, intelligent agents, or multi-model orchestration frameworks.

- Understanding of performance, cost, and reliability trade-offs in production AI systems.

- Familiarity with frameworks such as LangChain, LangGraph, CrewAI, or similar is a plus.

Cloud & Deployment :

- Experience deploying or operating AI-powered services on cloud platforms such as AWS, Azure, or GCP.

- Familiarity with monitoring, logging, and maintaining production services is desirable.

Professional Attributes :

- Strong problem-solving and analytical skills with the ability to work on ambiguous, evolving AI use cases.

- Ability to collaborate with cross-functional teams and communicate complex technical concepts clearly.

- A proactive mindset with a strong interest in emerging AI technologies and applied innovation.

- Comfortable working in a fast-paced, experimental environment where rapid iteration is expected.

Experience & Qualification :

- 2 - 4 years of experience in software engineering, data engineering, or applied AI development.

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field (or equivalent practical experience)