Agentic AI Innovator

1 week ago

Vizag, Andhra Pradesh, India beBeeArtificialintelligence Full time ₹ 15,00,000 - ₹ 20,00,000

At Twinamics, we are on a mission to revolutionize the way businesses operate by leveraging cutting-edge agentic AI technology. As an Artificial Intelligence Engineer, you will play a pivotal role in designing and implementing state-of-the-art AI systems that drive real-time intelligence and autonomous actions.

We transform data into actionable insights and execute business-critical decisions through our proprietary DIPPCAA Engine. This end-to-end Data-to-Action Infrastructure connects data, reasons over it, and executes decisions via AI Employees (AI-CXOs and their Agent Workforce).

Key Responsibilities
  • Agentic AI System Design: Design and implement agentic AI systems with stateful reasoning, memory, and orchestration.
  • Digital Twin AI Employees: Develop Digital Twin AI Employees (e.g., Finance CXO, Sales Lead) using LLMs, SLMs, and custom orchestration logic.
  • Enterprise Integration: Integrate AI agents with enterprise systems (ERP, CRM, WhatsApp, Accounting APIs, Voice Platforms).
  • Plug-and-Play AI Templates: Build plug-and-play AI templates for cross-industry use cases (hospitality, manufacturing, supply chain, logistics).
  • Scalability Optimization: Optimize for scalability: retries, fail-safes, state persistence, and performance tuning.
Required Skills and QualificationsCore AI & ML
  • Machine Learning and Deep Learning: Strong background in Machine Learning and Deep Learning (esp. time-series & sequential modeling).
  • LLMs and SLMs: Experience with LLMs, SLMs, or hybrid architectures for reasoning + prediction.
  • Probabilistic Modeling: Knowledge of probabilistic modeling (Bayesian methods, Monte Carlo, Markov Decision Processes).
  • Time-Series Forecasting: Experience in time-series forecasting (ARIMA, Prophet, RNN/LSTM/GRU, Transformer-based models).
  • Anomaly Detection: Familiarity with anomaly detection techniques to capture unexpected signals.
Prescriptive AI & Decisioning
  • Prediction to Prescription: Ability to move from prediction → prescription (recommend optimal actions, not just forecasts).
  • Reinforcement Learning: Knowledge of reinforcement learning, optimization algorithms, or decision theory.
  • Control Systems: Familiarity with control systems for closed-loop feedback in enterprise workflows.
Data Layer & Infra
  • Data Pipelines: Hands-on with data pipelines (ETL/ELT, Apache Kafka, Airflow, dbt, or similar).
  • Vector Databases: Experience with vector databases (Pinecone, Weaviate, Milvus, pgvector) for memory/state management.
  • Data Architecture: Strong SQL + NoSQL experience (Postgres, Mongo, etc.) for structured/unstructured data.
Enterprise Integration
  • API Design & Integration: Ability to connect models into ERP, CRM, Finance, and Supply Chain systems.
  • API Design: Strong API design & integration skills (REST, GraphQL, gRPC).

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