Highlights
AI-driven solutions, business process automation, stateful agents, efficient model serving, cloud deployment.
Description
Job Summary
pWe are seeking a motivated Jr. AI Developer to join our dynamic team, focusing on designing and deploying production-ready AI-driven solutions. This role involves analyzing business processes, building intelligent systems, and optimizing machine learning models.
Responsibilities
- Conduct business analysis for AI automation and design solutions accordingly
- Create and deploy advanced agentic workflows using frameworks like LangChain
- Develop robust Retrieval-Augmented Generation (RAG) pipelines for data retrieval
- Optimize large language models and serve them efficiently with vLLM
- Evaluate LLM application performance and debug issues
- Deploy AI solutions across cloud environments ensuring high availability
Required Skills
- Natural Language Processing (NLP)
- Open-source LLMs
- Docker for containerization
- Agentic workflows
- Cloud computing
Required Skills Explained
- Natural Language Processing (NLP): Essential for understanding and processing human language.
- Open-source LLMs: Experience with Hugging Face ecosystem, Transformers, Datasets for building AI applications.
- Agentic Frameworks: Proficiency in LangGraph, LangChain, AutoGen for developing stateful AI agents.
- RAG Pipelines: Knowledge of Retrieval-Augmented Generation pipelines for information extraction from proprietary data.
- Model Optimization & Serving: Expertise in self-hosting and serving large language models using vLLM for efficient deployment.
- Observability Tools: Experience with Langfuse or similar tools to monitor, evaluate, and debug LLM application performance.
- Cloud Computing: Proficiency in deploying scalable AI solutions across AWS, GCP, or Azure environments.
Who is this for
pThis role is ideal for candidates with a strong foundation in AI/ML and hands-on experience with NLP, open-source LLMs, and agentic frameworks. A passion for innovation and a desire to solve real-world problems through technology are essential.
Why This Job is a Good Opportunity
ulliOpportunity to work on cutting-edge AI/ML projects with industry-leading tools and technologies.liChance to collaborate with cross-functional teams and contribute to the development of innovative solutions for real-world business challenges.liPotential for growth in a dynamic and supportive environment that values continuous learning and improvement.liCompetitive salary and benefits package, including health insurance, retirement plans, and professional development opportunities.
Interview Preparation Tips
- Review key AI/ML concepts and NLP techniques thoroughly to demonstrate your foundational knowledge.
- Prepare examples of projects or personal work that showcase your experience with LLMs, LangChain, and RAG pipelines.
- Practice coding challenges related to Docker containerization and Git version control.
- Be ready to discuss the observability tools you have used for monitoring AI applications and how they improved performance.
Career Growth in This Role
pThis role offers significant growth potential as it requires a deep understanding of AI/ML principles and practical application. You can advance your career by taking on more complex projects, leading cross-functional teams, or even transitioning into a leadership position within the Data Science & Analytics department. The company's commitment to innovation ensures that you will be at the forefront of technological advancements.pAdditionally, opportunities for specialization in specific areas such as RAG systems, NLP frameworks, and cloud-native AI deployment can lead to specialized roles or even entrepreneurship in tech startups focused on AI solutions.
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Skills
Frequently Asked Questions
What kind of projects will I be working on?You’ll work on developing AI-driven solutions, building intelligent agents, and optimizing machine learning models for various business use cases.
Do I need experience with open-source LLMs?While previous experience is beneficial, the role focuses on hands-on training to get you up to speed with open-source LLM technologies.
Is there a lot of collaboration with other teams?Yes, this role requires close collaboration with cross-functional software engineering and product teams to deploy solutions into production.
