AI Systems Engineer

7 days ago

Dombivli, Maharashtra, India beBeeArtificial Full time ₹ 15,00,000 - ₹ 25,00,000

Our vision is to empower businesses with cutting-edge AI solutions.

We are building an autonomous brain for enterprises, transforming data into real-time intelligence and actionable insights.

At the core of our strategy is a proprietary engine that powers an end-to-end Data-to-Action Infrastructure, connecting data, reasoning over it, and executing business-critical decisions through AI Employees.

If you're excited to work at the frontier of agentic AI, orchestration frameworks, and enterprise-scale automation—this role is perfect for you.

Job Responsibilities
  • Design and implement agentic AI systems with stateful reasoning, memory, and orchestration.
  • Develop Digital Twin AI Employees using Large Language Models (LLMs), Sequence Learning Models (SLMs), and custom orchestration logic.
  • Integrate AI agents with enterprise systems, such as ERP, CRM, Finance, and Supply Chain APIs.
  • Build plug-and-play AI templates for cross-industry use cases, including hospitality, manufacturing, supply chain, and logistics.
  • Optimize for scalability: retries, fail-safes, state persistence, and performance tuning.
  • Collaborate with product designers and developers to bring enterprise-ready AI infrastructure to life.
Requirements

Core AI & ML:

  • Strong background in Machine Learning and Deep Learning, especially time-series and sequential modeling.
  • Experience with LLMs, SLMs, or hybrid architectures for reasoning and prediction.
  • Knowledge of probabilistic modeling, including Bayesian methods, Monte Carlo, and Markov Decision Processes.
  • Experience in time-series forecasting, such as ARIMA, Prophet, RNN/LSTM/GRU, and Transformer-based models.
  • Familiarity with anomaly detection techniques to capture unexpected signals.
  • Understanding of multi-signal fusion, including internal and external data streams.
  • Strong grasp of causal inference and correlation vs. causation for accurate event detection.

Prescriptive AI & Decisioning:

  • Ability to move from prediction to prescription, recommending optimal actions rather than just forecasts.
  • Knowledge of reinforcement learning, optimization algorithms, or decision theory.
  • Familiarity with control systems for closed-loop feedback in enterprise workflows.

Data Layer & Infra:

  • Hands-on experience with data pipelines, including ETL/ELT, Apache Kafka, Airflow, dbt, and similar tools.
  • Experience with vector databases, such as Pinecone, Weaviate, Milvus, and pgvector, for memory/state management.
  • Strong SQL and NoSQL experience, including Postgres and Mongo, for structured and unstructured data.
  • Data architecture skills, including schema design, feature engineering, real-time, and batch pipelines.

Enterprise Integration:

  • Ability to connect models into ERP, CRM, Finance, and Supply Chain systems.
  • Strong API design and integration skills, including REST, GraphQL, and gRPC.
Bonus Points
  • Exposure to knowledge graphs or graph databases, such as Neo4j and TigerGraph, for event relationships.
  • Familiarity with streaming data, including IoT, sensor data, and transaction logs.

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