AI Innovation Specialist

2 days ago

Mangalore, Karnataka, India beBeeArtificial Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

Artificial Intelligence Specialist

Twinamics is revolutionizing business operations with the Autonomous Brain for Enterprises.

We transform complex data into real-time intelligence and autonomous actions, empowering businesses to grow revenue without increasing headcount.

The DIPPCAA Engine drives an end-to-end Data-to-Action Infrastructure, connecting data, reasoning over it, and executing business-critical decisions through AI Employees.

If you're passionate about developing agentic AI systems, orchestration frameworks, and enterprise-scale automation, this role is ideal for you.

Main Responsibilities:

  • Create stateful AI systems with reasoning, memory, and orchestration capabilities.
  • Develop Digital Twin AI Employees using Large Language Models (LLMs), Sparse Large Memory (SLMs) models, and custom logic.
  • Integrate AI agents with enterprise systems (ERP, CRM, Accounting APIs, Voice Platforms).
  • Built plug-and-play AI templates for cross-industry use cases.
  • 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.

Necessary Skills:

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

Predictive Analytics & Decisioning:

  • Able to move from prediction → prescription (recommend optimal actions).
  • Knowledge of reinforcement learning, optimization algorithms, or decision theory.
  • Familiarity with control systems for closed-loop feedback in enterprise workflows.

Data Management & Infrastructure:

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

Enterprise Integration:

  • Able to connect models into ERP, CRM, Finance, and Supply Chain systems.
  • Strong API design & integration skills (REST, GraphQL, gRPC).

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