- Company Name
- Guidepoint
- Job Title
- Senior Software Engineer - AI Applications
- Job Description
-
**Job Title**
Senior Software Engineer – AI Applications
**Role Summary**
Lead end‑to‑end design, development, and deployment of scalable generative AI and data‑centric backend services. Drive product concepts from prototype to production, ensuring robust, observable, and maintainable systems that support advanced analytics and responsible AI capabilities.
**Expactations**
* Deliver high‑quality code and architecture that meets product timelines and performance targets.
* Collaborate across engineering, product, and business functions to clarify requirements and continuously improve product quality.
* Champion modern development practices, including CI/CD, containerization, caching, and observability.
* Mentor junior staff and contribute to knowledge sharing within the team.
**Key Responsibilities**
1. Design and implement core backend services and APIs using Node.js/TypeScript and Python.
2. Build and scale generative AI applications (LLMs such as GPT‑4, Claude, Gemini, or open‑weight models) with retrieval‑augmented generation, embeddings, and prompt orchestration.
3. Own end‑to‑end lifecycle: architecture, code, unit/integration testing, model training, deployment, monitoring, and iterative improvement.
4. Manage data infrastructure: design Elasticsearch/OpenSearch indices, optimize queries, and oversee cluster health.
5. Develop and maintain relational (PostgreSQL, MS SQL) and NoSQL (Elasticsearch, MongoDB) database schemas.
6. Implement CI/CD pipelines and containerized deployments through Docker and Kubernetes (Azure Kubernetes Service preferred).
7. Integrate messaging layers (RabbitMQ, Kafka) for data pipelines and event processing.
8. Enforce coding standards, security best practices, and compliance requirements for AI solutions in regulated environments.
**Required Skills**
* Proficiency in Python, JavaScript/TypeScript (Node.js, Express, AWS SDKs); familiarity with Go is a plus.
* Deep experience with cloud platforms (Azure, AWS, GCP) and Kubernetes.
* Strong grasp of microservice architecture, RESTful APIs, caching (Redis, Memcached), and queuing systems.
* Expertise in Elasticsearch/OpenSearch, Elastic Stack, and query optimization.
* Hands‑on experience developing, deploying, and scaling large‑language‑model (LLM) based applications.
* Knowledge of retrieval‑augmented generation, embeddings, agent orchestration, or prompt chaining.
* Solid understanding of CI/CD pipelines, Docker, and infrastructure as code.
* Exceptional problem‑solving, communication, and cross‑functional collaboration skills.
**Required Education & Certifications**
* Bachelor’s degree in Computer Science, Software Engineering, or related field (or equivalent professional experience).
* Certifications in cloud platforms (e.g., Azure Solutions Architect, AWS Solutions Architect) or Kubernetes (CKA/CKAD) are advantageous but not mandatory.