Data and AI Platform & Infrastructure software engineer at Element Solutions helping to build cloud-based applications for AI systems in production. Collaborating with AI/ML engineers for scalable workflows and performance improvements.
Responsibilities
Build and operate backend services, APIs, and web applications that enable AI in production.
Partner with AI/ML engineers to take models from prototype to scalable, secure production workflows.
Own features end-to-end — from rapid prototyping to production deployment across frontend, backend, and cloud infrastructure.
Automate delivery with CI/CD pipelines and continuously improve performance, reliability, and observability in cloud environments.
Requirements
Strong proficiency in Python for building and maintaining scalable backend services, APIs, automation, and data processing workloads, with advanced SQL expertise in relational modeling, complex queries, performance optimization, and transactional integrity.
Hands-on experience maintaining production codebases across both frontend and backend, and rapidly integrating prototype UIs into secure, scalable backend and infrastructure components to accelerate prototype-to-product delivery.
Experience with modern frontend frameworks (React, Vue, or Angular) and integrating frontend applications with backend APIs, authentication/authorization, and environment-specific configuration.
Proven experience designing, deploying, and operating applications on cloud platforms — Azure preferred, with AWS or GCP acceptable — including application hosting, serverless compute, container orchestration, and relational/object storage.
Strong understanding of secure cloud architecture patterns, including networking, secrets management (e.g., Azure Key Vault or equivalents), identity and access management, and least-privilege access controls.
Hands-on experience with Infrastructure as Code (IaC) (e.g., Terraform or native cloud templates), containerization (Docker), and cloud-native monitoring and observability.
Strong experience with Git-based version control, collaborative branching strategies, and building and maintaining CI/CD pipelines (e.g., Azure DevOps Pipelines, GitHub Actions), including automated testing, artifact management, and controlled deployment promotion.
Hands-on experience with NoSQL databases, particularly Azure Cosmos DB (Core SQL API, MongoDB API, or Table API)
Experience designing data access patterns for high-scale, low-latency distributed applications.
Experience building embedding-based semantic search using vector databases, with understanding of vector indexing, similarity search, and hybrid retrieval, e.g., Azure OpenAI embeddings + Azure AI Search or Cosmos DB vector indexing.
Experience designing and implementing Retrieval-Augmented Generation (RAG) pipelines for enterprise use cases such as document intelligence, semantic search, and internal knowledge assistants.
Familiarity with LLM application frameworks such as LangChain, Semantic Kernel, or LlamaIndex.
Awareness of LLM operational concerns including latency, token cost optimization, observability, and model lifecycle management.
Benefits
As part of our team here, in addition to a competitive Gross Salary you will be eligible to participate in a generous performance related bonus scheme.
In addition, you will receive 3 comprehensive insurance benefits 1. GMC (Self/ Spouse and 2 Kids – INR 5 Lakhs coverage), 2. GPA – 5 Times of Annual Salary sum assured for Employee, 3. GTLI - 5 Times of Annual Salary sum assured for Employee.
Also as an Employee benefit we offer free 2 meals on all working days.
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