Build production-grade agentic AI systems that reason, search, and execute workflows. Develop RAG pipelines, AI agents, semantic search layers, data processing solutions, dimensional data models, and scalable AI workloads. Work with structured and unstructured data, LLMs, vector databases, cloud infrastructure, CI/CD, and ML observability. Responsibilities include fine-tuning models, prompt engineering, optimizing context windows, and deploying reliable AI applications.
Anovia is an industry-leading technology outsourcing support provider with expertise in the telecommunications industry. Operating for over 20 years, we specialize in workflow and knowledge processes, as well as technical support, helpdesk and multilingual support services. With over 200 professional experts across the globe, we service some of the worlds' most successful Fortune 500 and Fortune 1000 companies.
About the role:We are looking for a hybrid AI and Data Engineer to build the next generation of "Agentic" systems. You will bridge the gap between raw structured/unstructured data and actionable AI, moving beyond simple chatbots to create autonomous agents that can reason, search, and execute complex workflows, including multi-agent systems and integrations with collaboration tools like Microsoft Teams or Google Chat.
Technical Qualifications:1. GenAI & Agentic Development
- LLM Orchestration: 2+ years building and deploying AI-driven applications. You should be an expert in end to end RAG pipeline design and Agentic AI development, using frameworks like LangChain, LangGraph, LlamaIndex, and multi-agent frameworks for complex reasoning tasks.
- Model Proficiency: Solid understanding of Transformer architectures (Gemini, GPT, Claude), with a focus on Google's LLM ecosystem. Comfortable working with API parameters for LLMs (temperature, top-p, token limits, function calling, etc.) to tune model behavior for production use.
- Experience with fine-tuning, advanced prompt engineering, and optimizing context windows.
- Vector Expertise: Proven ability to build semantic search layers using PG Vector, embedding models, and Google Indexing.
- Integration: Experience connecting AI agents to collaboration platforms such as Microsoft Teams or Google Chat, for workflow and notification use cases.
2. Data Engineering & Scale
- Big Data Stack: Experience processing large-scale datasets using Python (Pandas/PySpark) or Scala.
- Warehousing & SQL: Professional experience with Snowflake or Redshift, including the ability to write high-performance Advanced SQL.
- Data Modeling: Ability to design dimensional data models optimized for low-latency AI consumption and high data quality.
3. Software Craftsmanship
- Production Standards: Focus on writing clean, maintainable code with robust CI/CD practices and ML Observability.
- 5+ years of experience in relevant technology
- Education: B.Tech/M.Tech in Computer Science or a related field
- Cloud Infrastructure: Hands-on experience with AWS (Bedrock, Lambda) for deploying and scaling AI workloads
- Gemini Ecosystem: Direct experience leveraging Google Gemini for multimodal or long-context applications
- Comprehensive Health Insurance policy
- Employee Wellness Program with focus on mental health
- Robust reward and recognition programs
- Company incentive programs offered
- Attractive leave policy: Holiday Leave, Maternity Leave, Paternity Leave, Birthday leave, Bereavement Leave and Paid Leave for personal time off
- Ample growth and learning opportunities
- Remote work opportunities
- Focus on work/life balance
- Immigration Program supporting immigration to Canada for eligible employees
We thank all candidates for their interest, however, only those selected for an interview will be contacted.
Anovia is an equal opportunity employer and may use Artificial Intelligence tools to assist in reviewing and processing candidate applications.
Similar Jobs
Information Technology • Software • Consulting
Build and ship internal tools, backend services, APIs, frontend interfaces, data integrations, automation, and AI-powered features. Integrate LLM, RAG, and agent capabilities into usable software, collaborate with teams across the business, and own solutions through production. The role requires adaptable full-stack engineering, data fluency, AI integration experience, autonomy, and reliable end-to-end delivery.
Top Skills:
Ai ApisAPIsCi/CdContainersData PipelinesDatabasesInfrastructure-As-CodeLlmPythonRagTypescript
Cloud • Database
Build and deploy production-ready AI applications and data pipelines on Azure Databricks. Responsibilities include PySpark and SQL ETL/ELT, CI/CD, Azure integrations, ML and generative AI deployment, RAG and vector search, LLM fine-tuning, monitoring, optimization, governance, and responsible AI. The role also involves Databricks Apps, Unity Catalog, prompt engineering, FastAPI and React applications, testing, guardrails, and collaboration with data science and platform teams.
Top Skills:
Adls Gen2AirflowArmAzureAzure Cognitive SearchAzure Data FactoryAzure DatabricksAzure DevopsAzure FunctionsAzure Key VaultAzure Machine LearningAzure OpenaiBicepClaude ApisDatabricks Asset BundlesFaissFastapiHugging FaceLangchainLoraMlflowPysparkPythonQloraReactSQLTerraformUnity CatalogVisual Studio Code
Food • Mobile
Design and build scalable data and AI infrastructure for production LLM applications. Responsibilities include developing RAG systems, embedding and vector retrieval pipelines, AI agents, LLM evaluation and observability frameworks, and batch or streaming data platforms using Databricks, Spark, Snowflake, Delta Lake, and Airflow. The role also involves optimizing distributed workloads, establishing data governance and quality practices, and partnering with engineering and product teams to productionize AI capabilities.
Top Skills:
Ai AgentsApache AirflowSparkCi/CdDatabricksDatabricks Mosaic AiDatabricks Vector SearchDelta LakeEmbeddingsGenerative AiJavaKafkaLangchainLanggraphLlamaindexLlmsMlflowPineconePythonQdrantRagScalaSemantic SearchSnowflakeSpark Structured StreamingSQLUnity CatalogVector DatabasesWeaviate
What you need to know about the Chennai Tech Scene
To locals, it's no secret that South India is leading the charge in big data infrastructure. While the environmental impact of data centers has long been a concern, emerging hubs like Chennai are favored by companies seeking ready access to renewable energy resources, which provide more sustainable and cost-effective solutions. As a result, Chennai, along with neighboring Bengaluru and Hyderabad, is poised for significant growth, with a projected 65 percent increase in data center capacity over the next decade.
