Quick Take -
As an AI Engineer, you’ll drive the end-to-end development of advanced GenAI applications, including agentic AI agents with autonomous workflows, function calling, and LLM model fine-tuning. This role is for an experienced engineer who excels at building robust, production-grade AI systems and pushing the boundaries of what GenAI can accomplish.
The Work -
- Fine-tune and deploy open-source general purpose LLMs and code-generation models (e.g. Llama 4, qwen2.5) using PEFT, LoRA, QLoRA, instruction tuning, RLHF, etc..
- Design GenAI applications with agentic capabilities—autonomous, goal-driven agents that can plan, reason, and execute multi-step workflows with minimal human input.
- Implement function calling in workflows, enabling models to invoke external tools, APIs, databases, and services to perform actions or access real-time data.
- Build agentic RAG pipelines, where LLMs coordinate data retrieval and reasoning dynamically via retrieval-augmented generation.
- Create and maintain scalable pipelines, including data ingestion, labeling, feature engineering, vector DB management, and MLOps frameworks (MLflow, Kubeflow).
- Containerize applications using Kubernetes and Docker.
- Optimize and monitor model performance, including latency, drift, bias, privacy, and security compliance.
- Collaborate cross-functionally, mediating between data, product, and engineering teams to translate requirements into agentic GenAI solutions.
- Stay current with research trends like agentic RL frameworks (e.g., ARTIST), multi-agent orchestration, MCP, and secure function calling.
The Must-Haves -
- B.S or M.S. in Computer Science, Data Science, ML/AI or equivalent.
- 3-5 years building and deploying AI/ML solutions with demonstrable production experience.
- Extensive experience fine-tuning LLMs and code models with advanced techniques (PEFT/LoRA/QLoRa/RLHF).
- Proven track record designing or delivering agentic GenAI applications—function calling, autonomous workflows, RAG pipelines.
- Proficient in Python, PyTorch/TensorFlow, Hugging Face, LangChain, LangGraph or similar frameworks.
- Experience in Document and Image Analysis and extracting insights from unstructured data, including text documents and images.
- Strong infrastructure skills: Docker, Kubernetes, CI/CD, MLOps tooling.
- Sharp analytical mindset for system optimization, error mitigation, and security best practices.
- Excellent problem-solving and ability to translate business needs into technical design.
Over the years, we’ve discovered that the most effective and successful associates at apexanalytix are people who have a specific combination of values, skills, and behaviors that we call “The apex Way”. Read more about The apex Way -
We are currently unable to offer Visa Sponsorship; candidates must be authorized to work in the U.S. without sponsorship now as well as in the future.
Benefits
At apexanalytix we know that our associates are the reason behind our successes. We truly value you as an associate and part of our professional family. Our goal is to offer the very best benefits possible to you and your loved ones. When it comes to benefits, whether for yourself or your family the most important aspect is choice. And we get that. apexanalytix offers competitive benefits for the countries that we serve, in addition to our BeWell@apex initiative that encourages employees’ growth in six key wellness areas: Emotional, Physical, Community, Financial, Social, and Intelligence.
With resources such as a strong Mentor Program, Internal Training Portal, plus Education, Tuition, and Certification Assistance, we provide tools for our associates to grow and develop.