Build the AI-Native and Future

TuTeck Technologies is hiring a Salsify PXM Expert to design, implement, and support scalable product experience management and content syndication solutions. The role focuses on Salsify PXM configuration, syndication, and automation of product data workflows.
Location: Kolkata, West Bengal, India (onsite)

Roles and Responsibilities:
• Design, build, and configure applications on the Salsify platform, including custom development and UI enhancements.
•  Manage product data by importing, structuring, enriching, and maintaining data within Salsify data models and taxonomies.
•  Configure and optimize content syndication workflows to distribute accurate product content across retailer and marketplace channels.
•  Automate manual processes and enhance workflows using Salsify capabilities and AI-powered features where applicable.
•   Access control setup and Salsify Access control policy implementation.
•   Perform unit testing and User Acceptance Testing (UAT), troubleshoot issues, and provide ongoing application and integration support.
•      Collaborate with cross-functional teams to gather requirements and align solutions with business objectives.
•      Create and maintain technical documentation, including workflows, specifications, and user guides.
Required Skill and Experience:
•      3+ years of hands-on experience with Salsify PIM/PXM implementations and support.
•      Good understanding of PXM, PIM, DAM concepts, and digital commerce best practices.
•      Proficiency with Salsify PXM platform features, data models, workflows, and syndication capabilities.
•      Must have completed PIM Certification from Salsify. Syndication Certification from Salsify is preferrable.
•      Good to have experience in Salsify Intelligence suite.
•      Experience in CI/CD pipelines, including unit testing. Solid understanding of Agile and Scrum methodologies.
•      Programming experience with databases, data modeling, and SQL (preferred).
•      Working knowledge in APIs, JSON, XML, and web service integration frameworks.
•      Experience across the full Software Development Lifecycle (SDLC) using Agile delivery models.
•     Strong analytical, problem-solving, and communication skills for collaboration with technical and business teams.
•      Familiarity with cloud platforms.

Job Title: Databricks Data Engineer

Location: Kolkata, India (On-site)

Experience: 5–8 Years

Notice Period: Immediate Joiners

Job Summary:

We are looking for a skilled Databricks Data Engineer with hands-on experience in PySpark and SQL to join our data engineering team in Kolkata. The ideal candidate will design, develop, and maintain scalable data pipelines and analytics solutions using Databricks, Azure, or AWS environments.

Key responsibilities:

Develop and maintain: design and build scalable data architectures and pipelines to support analytics and business requirements using the most-appropriate tools, technologies and methodologies as well as documenting those solutions in appropriate documentation solutions.

Monitor and troubleshoot: support stakeholders with data issues, monitor existing solutions to ensure seamless operations and minimal downtime.

Optimise and manage: build with continuous improvement in mind and refactoring of existing solutions to ensure robust data pathways and future proof implementations.

Collaborate: Work with cross-functional teams (inside and outside of DX) and with stakeholders to understand data requirements and deliver appropriate solutions.

Share expertise: serve as a SME for best practices, tools and technologies, providing consultancy for stakeholders and teams alike.

Functional Knowledge:

Deep understanding of key data design principles, and appropriate technologies and languages to be able to implement solutions successfully, for example, medallion design, normalisation, SCDs, data lakes, SQL, Python, Git, DevOps etc.

Experience in working with data, transformation of data, and the systems that can be used to provide that transformation and provision of data to end users (e.g. Azure, Databricks, SQL Server etc.).

Desirable to have exposure to SAP but not essential, also some Power BI/Fabric knowledge would be useful.

Relevant degree and strong knowledge in appropriate design principles.

Desirable to have knowledge of LucidChart/diagramming/documentation methodologies.

Business Expertise:

Awareness of emerging technologies for innovation in the data lake space such as Fabric, Databricks, SAP Datasphere, Iceberg etc.

Some experience working with consumer sales data (e.g. master data, sales, forecast) would be useful.

Experience of multinational organisations, and cross functional/cross-cultural operations in these environments.

Education:

Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Engineering, or a related field.

Role Description

We are looking for a highly skilled Senior AI/ML Engineer to lead the development of our next-generation intelligence platforms. In this role, you will bridge the gap between traditional predictive modeling and cutting-edge Generative AI. You will be responsible for the full lifecycle of ML development—from data pipeline construction and model training to deployment and monitoring.

Ideal candidates will have deep hands-on experience with major deep learning frameworks and a strong passion for integrating Large Language Models (LLMs) and Small Language Models (SLMs) using RAG architectures.

Key Responsibilities

1. Model Development & Engineering

• Design, build, and deploy robust machine learning models using TensorFlow, PyTorch, or Keras for predictive analytics, classification, and computer vision/NLP tasks.
• Develop scalable data pipelines to pre-process, clean, and structure structured and unstructured data for model training.

2. Generative AI & RAG Implementation

• Architect and implement Retrieval-Augmented Generation (RAG) systems to ground LLM responses in proprietary company data.
• Orchestrate complex LLM workflows using frameworks like LangChain or LlamaIndex.
• Integrate third-party LLM APIs (OpenAI, Anthropic, Gemini) and open-source models (Llama 3, Mistral) into production applications.

3. Model Tuning & Optimization

• Fine-tune Small Language Models (SLMs) and LLMs for domain-specific tasks using techniques like LoRA, QLoRA, and PEFT to balance performance with computational efficiency.
• Optimize model inference latency and throughput for production environments (e.g., using ONNX, TensorRT).

4. MLOps & Deployment

• Collaborate with DevOps to containerize models (Docker/Kubernetes) and deploy them via TorchServe, TensorFlow Serving, or Triton Inference Server.
• Implement experiment tracking and model registry workflows using MLflow or Weights & Biases (W&B).

5. Technical Leadership

• Mentor junior developers and conduct code reviews.
• Translate complex business requirements into technical AI/ML specifications.

Required Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or a related field.
• Experience: 5–8 years of professional experience in Software Engineering with a specific focus on AI/ML.
• Mastery of Python and strong familiarity with libraries such as NumPy, Pandas, and Scikit-learn.
• Extensive hands-on experience with TensorFlow (preferred) or PyTorch (Experience with both is a strong plus).
• Strong knowledge of Pattern Recognition and Neural Networks
• Solid foundation in Computer Science and Algorithms
• Proficiency in Statistics and machine learning concepts
• Experience in deploying machine learning models in production environments
• Strong understanding of NLP techniques (Tokenization, Embeddings, Transformers, Attention Mechanisms).
• Proficiency in SQL and experience handling large datasets.

Preferred Experiences

• GenAI Stack: Experience with frameworks like LangChain, LlamaIndex, or Haystack.
• Vector Databases: Hands-on experience with vector stores such as Pinecone, Milvus, Weaviate, ChromaDB or FAISS.
• Model Tuning: Proven track record of fine-tuning open-source models (e.g., Hugging Face transformers) on custom datasets.
• Cloud AI: Experience with AWS SageMaker, Azure AI Studio, or Google Vertex AI.
• Big Data: Experience handling large-scale datasets using Apache Spark or Databricks.

Soft Skills & Competencies

• Problem Solver: Ability to break down ambiguous problems into solvable algorithmic components.
• Continuous Learner: The AI landscape changes weekly; you must demonstrate a hunger to keep up with the latest papers and techniques.
• Communication: Ability to explain complex model behaviors to non-technical stakeholders.