JOB DESCRIPTION

AI Engineer Development & Integration

Design, develop, and deploy AI-driven applications and features using LLM APIs (Gemini, Claude, OpenAI) and related SDKs.

Build and maintain robust integration pipelines between AI services and internal/external systems (REST APIs, webhooks, middleware).

Develop prompt engineering strategies, fine-tuning workflows, and retrieval-augmented generation (RAG) pipelines for production use cases.

Evaluate, benchmark, and select the most suitable AI models and providers based on performance, cost, latency, and accuracy requirements.

Collaborate with product managers, data scientists, and backend engineers to translate business requirements into scalable AI solutions.

Implement monitoring, logging, and observability for AI services to ensure reliability and performance in production environments.

Stay current with the rapidly evolving AI/ML landscape and proactively recommend new tools, techniques, and best practices.

Write clean, well-documented, and testable code following software engineering best practices.

Contribute to architecture decisions for AI infrastructure, including model serving, caching, and cost optimization.

Required Qualifications

Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.

37 years of professional software development experience with strong proficiency in Python, JavaScript/TypeScript, or similar languages.

Demonstrated hands-on experience integrating and building applications with at least two of the following: Google Gemini API, Anthropic Claude API, OpenAI API.

Solid understanding of RESTful API design, microservices architecture, and cloud platforms (AWS, GCP, or Azure).

Experience with vector databases (Pinecone, Weaviate, ChromaDB), embedding models, and RAG architectures.

Proficiency with version control (Git), CI/CD pipelines, and containerization (Docker, Kubernetes).

Strong problem-solving skills with the ability to work independently and collaboratively in a fast-paced environment.

Preferred Qualifications (Nice to Have)

AI/ML-related certifications such as:

Google Cloud Professional Machine Learning Engineer

AWS Certified Machine Learning Specialty

DeepLearning.AI / Coursera AI Specializations

Anthropic Claude or OpenAI partner certifications

Experience with LangChain, LlamaIndex, Semantic Kernel, or similar AI orchestration frameworks.

Familiarity with model fine-tuning, RLHF, and training data pipeline management.

Knowledge of AI safety, responsible AI practices, and content moderation strategies.

Experience with multi-modal AI applications (vision, audio, text).

Contributions to open-source AI projects or published research in AI/ML.

Technical Environment

Languages: Python, TypeScript/JavaScript, SQL

AI Platforms: Google Gemini, Anthropic Claude, OpenAI (GPT-4 / GPT-4o)

Frameworks: LangChain, FastAPI, Next.js, Flask

Cloud: AWS / GCP / Azure

Databases: PostgreSQL, Redis, Pinecone, ChromaDB

DevOps: Docker, Kubernetes, GitHub Actions, Terraform