AI Engineer OmnifiCX Hyderabad, India

Kensium Llc; Hyderabad; On-site; INR 1,000,000 - 1,500,000; Full time

Benefits offered by this job

Mentorship and coaching

Flexible work options

Job summary

Kensium Llc in Hyderabad is seeking an experienced AI Engineer to design and deploy AI-driven capabilities for their commerce platform. This role involves collaborating with product, engineering, and data teams to turn business challenges into robust AI solutions, leveraging advanced machine learning techniques and large language models.

Ideal candidates should have 4–8 years in AI/ML, including practical experience in integrating ML systems. Competitive benefits include mentorship opportunities and flexible work arrangements.

Qualifications

• 4–8 years in AI/ML engineering, with 2 years delivering production ML systems.
• Hands-on experience with supervised, unsupervised, and reinforcement learning.
• Strong Python skills and proficiency in Pandas, NumPy, and ML experimentation tooling.

Responsibilities

• Design, train, and deploy machine learning models for commerce use cases.
• Integrate large language models into product workflows.
• Develop rule-augmented ML models for order routing.

Skills

Machine Learning

AI Integration

Python

Data Engineering

Collaboration Tools

Education

B.Tech / B.E. or M.Tech in Computer Science, Data Science, Mathematics, or a related field

Tools

Apache Spark

AWS

dbt

Job description

As an AI Engineer at OmnifiCX, you will design, build, and deploy intelligent AI-driven capabilities that power our commerce platform. You will work at the intersection of machine learning, backend engineering, and product intelligence — delivering features like smart order routing, predictive analytics, conversational AI assistants, and automation pipelines. You will collaborate closely with product, engineering, and data teams to translate business problems into production-grade AI solutions.

• Design, train, and deploy machine learning models for commerce use cases such as order routing optimization, demand forecasting, fraud detection, and customer intent prediction.
• Build and maintain end-to-end ML pipelines covering data ingestion, feature engineering, model training, evaluation, and serving.
• Experiment with state-of-the-art approaches including LLMs, transformers, and classical ML algorithms depending on the problem context.

LLM & Generative AI Integration:

• Integrate large language models (e.g., OpenAI GPT, Anthropic Claude, open-source models via Hugging Face) into OmnifiCX product workflows such as intelligent order assistants, auto-summarization, and natural language query interfaces.
• Design prompt engineering strategies, RAG (Retrieval-Augmented Generation) pipelines, and agentic workflows for commerce-specific scenarios.
• Evaluate and benchmark LLM outputs for accuracy, latency, cost, and safety before production rollout.

AI-Powered Order Routing & Optimization:

• Collaborate with the OMS product team to embed AI into the order routing engine — building models that optimise routing decisions based on inventory, SLAs, cost, carrier performance, and real-time signals.
• Develop rule-augmented ML models that work alongside deterministic business logic in the routing module.
• Monitor model performance in production and implement feedback loops for continuous improvement.
• Build and maintain data pipelines for structured and unstructured commerce data.
• Work with data and platform teams to define feature stores, data schemas, and batch/streaming data flows for model training and inference.
• Ensure data quality, lineage, and reproducibility across ML experiments.
• Work closely with product managers, backend engineers, and business analysts to scope and deliver AI features aligned with OmnifiCX roadmap priorities.
• Mentor junior engineers on AI/ML best practices and promote a culture of data-driven decision making.
• Document AI system designs, model cards, and experiment outcomes for cross-functional transparency.

Experience and Skills:

Minimum:

• Experience: 4–8 years in AI/ML engineering, with at least 2 years delivering production ML systems.
• Machine Learning: Hands‑on experience with supervised, unsupervised, and reinforcement learning. Proficiency in scikit‑learn, XGBoost, LightGBM, and deep learning frameworks (PyTorch or TensorFlow).
• LLMs & Generative AI: Practical experience integrating LLM APIs (OpenAI, Anthropic, Cohere, or open-source). Familiar with LangChain, LlamaIndex, prompt engineering, and RAG pipeline design.
• Programming: Strong Python skills. Proficiency in Pandas, NumPy, and ML experimentation tooling.
• Data Engineering: Experience building pipelines using Apache Spark, Airflow, or dbt. Comfortable with SQL and large structured datasets.
• Model Serving & APIs: Experience deploying ML models as REST/gRPC microservices using FastAPI or Flask.
• MLOps: Experience with model monitoring, versioning, and CI/CD for ML pipelines.
• Cloud Platforms: Hands‑on experience with AWS or GCP/Azure equivalents.
• Optimization Problems: Ability to frame business problems as optimization or ranking tasks.
• Collaboration Tools: Familiarity with Jira, Confluence, or similar tools.

Preferred:

• Certifications: AWS Certified Machine Learning – Specialty, Google Professional ML Engineer, or equivalent.
• Commerce / OMS Domain: Exposure to e‑commerce, order management, supply chain, or logistics AI use cases.
• Vector Databases: Experience with Pinecone, Weaviate, Chroma, or pgvector.
• Agentic AI: Experience designing multi‑step agentic workflows.
• Streaming Data: Exposure to Kafka or Kinesis.

Minimum Qualifications:

• B.Tech / B.E. or M.Tech in Computer Science, Data Science, Mathematics, or a related field.
• Strong analytical thinking.
• Ability to thrive in a fast‑paced environment.
• Demonstrated track record of taking ML projects from prototype to production.

What’s in it for you?

• Work on high‑impact AI problems.
• Mentorship and coaching.
• Flexible work options.