Associate AI Developer

Responsibilities

• Build AI services: Develop and help deploy services and microservices that integrate LLMs and classical ML (real-time APIs, batch, and event-driven workloads).
• Agentic & orchestration: Contribute to agent workflows and tool-use orchestration using frameworks such as LangChain, with structured I/O via Pydantic.
• Vision & deep learning: Help develop and integrate CNNs and vision models (classification, detection, OCR) into production pipelines.
• Observability: Instrument services with logging, tracing, and evaluation hooks; help monitor quality, latency, cost, and drift.
• Cloud-agnostic delivery: Build AI integrations on AWS, Azure, or NVIDIA tooling—and with open-source models—favoring portable, well-tested code.
• Quality & collaboration: Write tests from specs, join code reviews and design discussions, and respond constructively to feedback.

Qualifications

• Education: Recently graduated from, a degree/certificate program in Computer Science, AI/ML, Data Science, Engineering, or a related field.
• Experience: Up to 2 years of practical experience (internships, co-ops, or substantial academic/personal projects) developing software or AI applications.
• AI cloud services: Hands-on exposure building AI services and integrations with one or more of: AWS (Bedrock, SageMaker), Azure (AI Foundry/AI Studio, Azure OpenAI), NVIDIA (CUDA, NIM, Triton), or open-source (LangChain, Pydantic, Python).
• Programming: Solid Python foundation plus software engineering fundamentals (version control, testing, APIs, clean code).
• Mindset: Cloud-agnostic and portability-minded; strong problem-solver; open to learning and feedback in a fast-paced environment.

Preferred Skills

• Familiarity with agentic patterns, tool-use orchestration, or the Model Context Protocol (MCP); RAG and vector search (Pinecone, Weaviate, FAISS).
• Exposure to deep learning frameworks (PyTorch, TensorFlow), MLOps/observability (MLflow, OpenTelemetry), containers (Docker, Kubernetes), or CI/CD.
• Prior internship, capstone, or project work involving AI, data, or cloud services.