What are the responsibilities and job description for the Lead AI Engineer – AI Foundations, LLM Core & Agentic AI/Remote position at Apetan Consulting?
Job Title: Lead AI Engineer – AI Foundations, LLM Core & Agentic AI
Location- Remote
Role Summary
We are seeking a Lead AI Engineer to drive the design and development of advanced AI systems, with a focus on foundational models, Large Language Models (LLMs), and agentic AI frameworks. This role will lead the architecture and deployment of scalable, production-grade AI solutions that power intelligent automation and next-generation applications.
Key Responsibilities
- Lead the design and development of AI/ML systems with a focus on LLMs and agent-based architectures.
- Build and optimize pipelines for training, fine-tuning, and deploying large language models.
- Architect AI platforms supporting retrieval-augmented generation (RAG), embeddings, and vector databases.
- Develop and manage agentic workflows, orchestration layers, and multi-agent systems.
- Integrate AI capabilities into enterprise applications via APIs and microservices.
- Ensure scalability, performance, and reliability of AI systems in production.
- Collaborate with data scientists, software engineers, and product teams to deliver AI-driven solutions.
- Establish best practices for prompt engineering, model evaluation, and responsible AI.
- Implement monitoring, logging, and continuous improvement for deployed AI systems.
- Stay up to date with advancements in generative AI, LLM frameworks, and tooling.
Required Skills & Qualifications
- Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or related field.
- 7–10 years of experience in software engineering/AI engineering, with strong hands-on expertise in ML systems.
- Deep understanding of:
- Large Language Models (LLMs) and transformer architectures
- NLP, embeddings, and semantic search
- Retrieval-Augmented Generation (RAG)
- Strong programming skills in Python (preferred) and experience with ML frameworks (PyTorch, TensorFlow).
- Experience with LLM ecosystems and tools (e.g., LangChain, LlamaIndex, vector DBs like Pinecone, FAISS).
- Knowledge of API design, microservices, and distributed systems.
- Experience with cloud platforms (Azure, AWS, or Google Cloud Platform) and MLOps practices.
Preferred Qualifications
- Experience working with open-source and proprietary LLMs (e.g., GPT, LLaMA, etc.).
- Exposure to agentic AI frameworks and autonomous systems.
- Knowledge of fine-tuning techniques (LoRA, RLHF, etc.).
- Experience with Kubernetes, Docker, and scalable deployment architectures.
- Familiarity with AI safety, governance, and ethical AI principles.
Key Competencies
- Technical leadership and architecture design
- Innovation and problem-solving mindset
- Strong collaboration and communication skills
- Ability to translate business problems into AI solutions
- Mentorship and team development
Nice to Have
- Experience building AI platforms or internal AI tooling
- Contributions to open-source AI projects
- Background in data engineering or big data technologies