AI Engineer

4 weeks ago

Bengaluru, Karnataka, India DecisionX AI Full time
About DecisionX

At DecisionX, we are pioneering a new category:

World's first Decision AI — an AI Super-Agent that helps CXOs and Leadership at high-growth teams make smarter, faster decisions by turning fragmented data into clear next steps.

From bold bets in the boardroom to cross-functional decisions across Sales

& Marketing — down to the micro-decisions that power daily execution — Decision AI becomes your invisible co-pilot: thinking with you, acting ahead of you, and evolving beyond you.

System of Records | System of Intelligence | System of Actions

Role Description

We are looking for a passionate and hands-on AI Engineer to join our Founding team. You will work closely with some of the best Minds in AI to build the intelligence layer of our proprietary " Agentic Number System "

Key Responsibilities

- Build, fine-tune, and deploy AI/ML models for tasks like segmentation, scoring, recommendation, and orchestration.
- Ability to write Agents using LangGraph, LangChain.
- Develop and optimize agent workflows using LLMs (OpenAI, Claude, Mistral, etc.) for contextual reasoning and task execution.
- Create vector-based memory systems using tools like FAISS, Chroma, or Weaviate.
- Work with APIs and connectors to integrate third-party data (e.g., Salesforce, HubSpot, GSuite, Snowflake).
- Design pipelines that convert structured and unstructured signals into actionable insights.
- Collaborate with GTM and product teams to define real-world use cases for AI agents.
- Stay updated on the latest in LLMs, retrieval-augmented generation (RAG), and agent orchestration frameworks (e.g., CrewAI, AutoGen, LangGraph).

Must Have Skills

- 5-8 years of experience in AI/ML engineering or applied data science.
- Good Knowledge of AI System Design.
- Strong programming skills in Python, with proficiency in LangGraph, LangChain, Pandas, NumPy, and Scikit-learn.
- Experience with LLMs (OpenAI, Anthropic, etc.), prompt engineering, and RAG pipelines.
- Familiarity with vector stores, embeddings, and semantic search.
- Experience in data wrangling, feature engineering, and model deployment.
- Knowledge of MLOps tools such as MLflow, Weights & Biases, or similar.

What you will get ?

- Opportunity to shape the AI architecture of a high-ambition startup.
- Close collaboration with a Founder and a group of accomplished Ai dreamers.
- Ownership, autonomy, and the thrill of building something from 0 to 1.
- Early team equity and fast growth trajectory.

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