Job Description
About the Team
We are building a data-driven organization where analytics and intelligent automation sit at the center of strategic decision-making. Our team develops high-impact solutions across operations, product, marketing, client experience, and workforce performance. We combine modern data platforms with applied machine learning to support scalable, insight-driven growth.
If you are excited to apply natural language processing, large language models, and data engineering to solve meaningful business problems, this role provides the opportunity to work on highly visible initiatives with real-world impact.
Who You Are
You are a software engineer with deep experience in applied AI, particularly in building production systems powered by large language models (LLMs), natural language processing (NLP), and agent-based automation. You are comfortable operating in environments that require both structured enterprise rigor and innovative experimentation. You are motivated to grow into senior technical leadership roles in AI.
Key Responsibilities
- Design, build, and deploy agentic AI systems leveraging LLMs, NLP, and retrieval-augmented generation (RAG) pipelines for internal and external use cases.
- Partner with data scientists, product managers, and engineering teams to translate business problems into scalable AI solutions.
- Develop and maintain APIs and microservices (Python and / or Java) that integrate AI functionality into enterprise systems.
- Apply MLOps best practices to ensure reproducibility, observability, and seamless deployment of models into production environments.
- Stay current with advancements in generative AI, multi-agent orchestration, reinforcement learning, and emerging frameworks.
- Contribute to a culture of responsible AI adoption, including security, compliance, and ethical model governance.
- Mentor junior developers and contribute to the growth of the internal AI / ML engineering talent pipeline.
Required Qualifications
3-9 years of professional experience in software engineering, applied machine learning, or AI product development.Proficiency in Python and Java, with demonstrated experience delivering production-quality systems.Strong background in NLP, LLMs, and generative AI, including prompt engineering, fine-tuning, and orchestration.Practical experience with MLOps tooling, Docker / Kubernetes, and CI / CD pipelines.Experience working with structured and unstructured datasets.Strong communication skills, with the ability to clearly explain technical concepts to non-technical audiences.Preferred Qualifications
Experience in both enterprise and high-growth or startup-style environments, balancing structure with agility.Hands-on experience with cloud platforms (Azure, AWS, or GCP) and vector databases.Familiarity with agentic AI frameworks, autonomous workflow design, or multi-agent systems.Background in regulated industries such as insurance, financial services, or healthcare.Experience integrating AI capabilities into mission-critical, client-facing applications.Security & Privacy Responsibilities
Uphold organizational standards for data security and client privacy.Ensure ML pipelines, data flows, and model deployment processes are built with security and compliance in mind.Promote a security-first mindset across the data science and engineering teams.Report any suspected data or privacy incidents promptly in accordance with internal protocols.