AI/ Machine Learning Engineer
Job description
AI/ Machine Learning Engineer at Aeratechnology.
About the role
Aeratechnology is building the Aera Decision Cloud to automate and digitize enterprise decision-making. We are seeking an engineer to define the technical strategy for agentic AI within our platform. This role requires someone who has successfully moved autonomous agents into production, managed their failure modes, and implemented the necessary guardrails to ensure reliability.
Key facts
What you'll do
- Architect and build end-to-end agentic workflows, including multi-step reasoning, tool orchestration, and autonomous loops with human-in-the-loop checkpoints.
- Develop evaluation harnesses before building agents, including offline and online testing, golden datasets, and regression gates.
- Optimize agent performance and costs through prompt caching, context compression, model routing, and structured outputs.
- Build observability and tracing tools to profile agent behavior and identify bottlenecks.
- Design tool surfaces and skill sets for models, including MCP servers.
- Operationalize data science by integrating models into serverless infrastructure and production pipelines.
- Implement security measures such as sandboxing, tool permissioning, and prompt-injection defenses.
Requirements
- B.E./B.Tech in Computer Science, Computer Engineering, or a related field.
- 3 to 5 years of experience in software engineering and architecture.
- Minimum 2 years of experience designing and deploying ML or LLM-based systems, with 6 to 12 months specifically focused on LLMs.
- Proven experience owning complex, high-stakes systems from initial architecture through to production reliability.
- Hands-on experience with agentic coding tools and a deep understanding of current practices like agent memory, subagent patterns, and LLM-as-judge.
- Proficiency in Python and production services using FastAPI.
- Experience with large datasets, distributed systems (Ray, Spark), and ML libraries (PyTorch, Hugging Face, scikit-learn, pandas).
- Familiarity with containerized microservices (Docker, Kubernetes) and CI/CD tools (Git, Jenkins, Jira).
Nice to have
- Proficiency in GoLang.
- Experience with vector databases (Opensearch, Pinecone, Weaviate, FAISS, pgvector).
- Knowledge of event streaming and caching (Kafka, Pulsar, Redis).
- Experience with durable execution platforms like Temporal.
- Familiarity with observability tools (Langfuse, LangSmith, OpenTelemetry, MLflow, W&B, DVC).
- Experience with fine-tuning models and multi-modal AI workflows.
- Background in serverless AI infrastructure on AWS, GCP, or Azure.
Skills & tools
- Python, FastAPI, PyTorch, Hugging Face, scikit-learn, pandas.
- Ray, Spark, Docker, Kubernetes, Git, Jenkins, Jira.
- Agentic frameworks (LangGraph or similar).
Practical notes
Aeratechnology is a Series D startup established in 2017 with headquarters in Mountain View, California. We provide competitive salaries, company stock options, comprehensive medical coverage, group insurance, term insurance, accidental insurance, paid time off, and maternity leave. Employees have access to unlimited online professional courses and management development programs. Our office environment includes a fully-stocked kitchen and flexible working arrangements. We are an equal opportunity employer.