AI Engineer
AI Engineer
NeST Digital- Posted 5 hours ago
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Job Description
Key Responsibilities
Mandatory
Frontend, Dashboarding & Visualization
Mandatory
- Build data-driven web applications including micro-frontends, dashboards, interactive visualizations, alerts, KPIs and reporting views.
- Develop scalable APIs and backend services to process and expose telemetry, analytics, alerts and AI/ML outputs from system likes ThingsBoard, time-series databases and data lakes.
- Turn complex telemetry and model outputs into clear insights through meaningful charts, trends, aggregations, summaries and reports.
- Design production-grade services using service-oriented/microservices and event-driven architecture, with appropriate asynchronous processing and integration patterns.
- Ensure production readiness through scalability, multi-tenancy, observability, secure coding, performance optimization, fault handling and monitoring.
- Integrate with ML/AI, OT and platform services and iterate rapidly with pilot customers to deliver and refine the MVP.
Mandatory
Frontend, Dashboarding & Visualization
- Strong modern frontend development using React, Angular, Vue or equivalent.
- Hands-on experience building dashboards, analytics applications and reporting interfaces using real-world data.
- Experience with interactive data visualization, including charts, trends, KPIs, alerts and time-series views.
- Working knowledge of at least one visualization/dashboarding technology such as ECharts, Plotly, D3.js, Grafana, Kibana or equivalent.
- Strong backend/API development using Node.js, Python, Java or equivalent.
- Hands-on experience with REST APIs, JSON, authentication, authorization and service integration.
- Understanding of service-oriented/microservices architecture and scalable API design.
- Understanding of event-driven and asynchronous processing concepts.
- Working knowledge of SQL and data modelling.
- Practical familiarity with NoSQL and/or time-series databases.
- Experience handling large, dynamic or time-series data, including querying, aggregation and transformation.
- Hands-on Docker/containerization and CI/CD experience.
- Understanding of cloud deployment, scalability, performance and production troubleshooting.
- Practical familiarity with application observability, including logs, metrics and monitoring.
- Ability to use dashboards, logs and monitoring data to troubleshoot production issues.
- Secure coding and API security fundamentals, including authentication, authorization, input validation and secrets management.
- Understanding of multi-tenant application concepts, including tenant-aware access and data isolation.
- Experience with ThingsBoard or similar IoT/telemetry platforms.
- Experience with Grafana, Kibana, ELK/Elastic Stack, Loki, Prometheus, OpenTelemetry, Jaeger, Tempo, Dynatrace, AppDynamics, CloudWatch or equivalent.
- Experience integrating applications with log aggregation, monitoring, APM and distributed tracing platforms.
- Familiarity with Kafka, MQTT or equivalent messaging/event platforms.
- Experience with time-series databases such as TimescaleDB, InfluxDB or equivalent.
- Experience with data lakes and high-volume telemetry platforms.
- Familiarity with RAG, LLM APIs and Agentic AI.
- Experience with Kubernetes and cloud-native architectures.
- Domain exposure to Energy, Industrial Power or OT systems.
Mandatory
- 4+ years of professional full-stack development experience building and deploying production applications.
- Strong hands-on capability across frontend, backend and database layers, with the ability to work independently across the stack.
- Demonstrated experience building data-driven dashboards, visualization, analytics or reporting applications.
- Experience developing production-grade, scalable and secure applications.
- Practical experience with cloud environments, Docker and CI/CD.
- Strong production troubleshooting and problem-solving capability, including the ability to diagnose issues across application, API, data and infrastructure layers.
- Ability to work in a fast-moving MVP environment, prototype quickly and incorporate customer/pilot feedback.
- Strong communication and collaboration skills for working with ML/AI, data, OT and platform engineering teams.
- Experience building products for telemetry, IoT, analytics, monitoring or operational use cases.
- Experience integrating with observability and monitoring ecosystems, rather than only implementing application-level logging.
- Experience with multi-tenant SaaS platforms at production scale.
- Experience with event-driven/distributed systems and high-volume data applications.
- Experience integrating AI/ML model outputs or GenAI capabilities into production applications.
- Energy, Industrial Power or OT domain experience is an advantage, but not mandatory.
More Info
Key Skills
About Company
Skills:
bedrock , S3, Lambda, Docker, Terraform, Python, AWS, Api Gateway, Rust, Cloudformation, ECS, Iam, Go, Pinecone, Retrieval-Augmented Generation, LangGraph, Microsoft GraphQL, Step Functions, LLMs, TrueAgent, SageMaker, FAISS, Neo4G, TrueRAG
Skills:
Spring Boot, Containers, Microservices, Angular, Dependency Injection, Databases, Openshift, Java, Web Applications, Apis, Oauth2, Jwt, Testing Frameworks, J2EE, Devops Automation, Kubernetes, MVC Patterns, Context Assembly, Automated Quality Compliance Controls, Regulatory Compliance, Cloud Adoption, AI Risk Security, RAG, AI Engineering, Prompt Engineering, Modular Architecture
Skills:
Kafka, Sql, Tensorflow, Nlp, Pandas, Pytorch, Spark, FastAPI, Python, Ocr, Airflow, scikit-learn, TesserAct, React Next.js, Java Spring Boot
Skills:
Python, AWS, Generative AI, Agentic AI, Azure AI, CI/CD
Skills:
Pytest, Data Modeling, Rest Apis, Python, Sql, Microservices, Data processing libraries, Git-based development, Test automation frameworks