{"id":2189017,"url":"https://alion.io/job/intraedge-data-engineer-aiml-engineer","title":"Data Engineer - AI/ML Engineer","company":{"id":62138,"name":"IntraEdge","domain":"intraedge.com","url":"https://alion.io/company/intraedge","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":20000,"max_usd":42000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":56},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EKS","optional":false},{"name":"Apache Kafka","optional":false},{"name":"ArgoCD","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"DNS","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Google Cloud Spanner","optional":false},{"name":"Google GKE","optional":false},{"name":"Grafana","optional":false},{"name":"GraphQL","optional":false},{"name":"HashiCorp Vault","optional":false},{"name":"HIPAA","optional":false},{"name":"IAM","optional":false},{"name":"Java","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"Least Privilege","optional":false},{"name":"NLP","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prometheus","optional":false},{"name":"Pulumi","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"SOC 2","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Terraform","optional":false},{"name":"Vertex AI","optional":false},{"name":"FinOps","optional":true},{"name":"GitOps","optional":true},{"name":"gRPC","optional":true},{"name":"LangChain","optional":true},{"name":"LLM","optional":true}],"status":"live","first_seen_at":"2026-10-08T17:42:52Z","employer_posted_date":null,"last_verified_at":"2026-10-08T17:42:52Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"Job Title: Data Engineer - AI/ML Engineer\nLocation: Remote/Pune\nJob Type: Full Time\nThe shift timing: 2pm to 11pm \n\nResponsibilities\nDesign, build, and maintain scalable data pipelines to support analytics, ML, and operational reporting.\nDevelop robust data ingestion, transformation, and integration workflows using Python, SQL, and modern data engineering frameworks.\nBuild and maintain batch and streaming data pipelines leveraging technologies such as Kafka (or similar pub/sub tools).\nWork with Google Cloud Platform (GCP) services, including Cloud Storage, Dataflow, Pub/Sub, BigQuery, Cloud Spanner and Cloud Functions.\nDevelop and manage data APIs and interfaces (REST and GraphQL) to enable high-performance data access across microservices.\nImplement CI/CD automation for data pipelines using GitHub Actions, Argo CD, or equivalent tools.\nCollaborate with Data Scientists and MLOps teams to integrate ML/NLP models into data pipelines and production workflows.\nBuild and operationalize NLP data pipelines for structured and unstructured data sources (e.g., Rx claims, clinical documents).\nEnable continuous learning and model-retraining workflows using Vertex AI, Kubeflow, or similar GCP-native tooling.\nImplement frameworks for observability and data quality, ensuring ML predictions, confidence scores, and fallback events are logged into data lakes or monitoring systems.\nSupport distributed data systems and ensure reliability, performance, and scalability of data infrastructure.\nInfrastructure Engineering Responsibilities\nDesign and provision cloud infrastructure using Infrastructure as Code (IaC) tools such as Terraform or Pulumi for GCP resources including GKE clusters, Cloud SQL, VPC networks, IAM, and storage.\nDeploy, configure, and manage containerized data workloads using Kubernetes (GKE) — including deployments, autoscaling (HPA/VPA), namespaces, resource quotas, and health checks.\nArchitect and maintain network topology for data platform environments — VPCs, subnets, firewall rules, private service access, Cloud NAT, and VPC Service Controls.\nImplement and enforce IAM policies, service account governance, and secrets management (GCP Secret Manager or HashiCorp Vault) to ensure least-privilege access across all data services.\nBuild and maintain infrastructure monitoring and alerting using Cloud Monitoring, Prometheus, Grafana, or equivalent — covering pipeline latency, throughput, error rates, and resource utilization.\nEstablish and maintain CI/CD pipelines for infrastructure changes using Terraform Cloud, GitHub Actions, or Argo CD, ensuring infrastructure drift detection and rollback capability.\nManage environment parity (dev/staging/prod) for data platform infrastructure, including environment-specific configuration management and promotion workflows.\nDrive cloud cost governance — right-sizing compute resources, implementing committed-use discounts, setting up budget alerts, and producing cost attribution reports per workload.\nDesign and implement disaster recovery, backup, and high-availability strategies for data stores, pipeline infrastructure, and ML serving endpoints.\nCollaborate with Security and Platform teams to ensure data infrastructure compliance with enterprise security policies, SOC 2, HIPAA, and CVS Health regulatory requirements.\nRequired Qualifications\n5+ years of experience building data pipelines or backend data workflows using Python, Java, or similar languages.\n2+ years of experience designing REST/GraphQL data services or integrating data APIs.\nHands-on experience working with ML/AI model integration in production (e.g., Vertex AI Endpoints, TensorFlow Serving, ML REST APIs).\nExperience handling structured and unstructured datasets, including healthcare data (Rx claims, clinical documents, NLP text).\nFamiliarity with the end-to-end ML lifecycle: data ingestion, feature engineering, training, deployment, and real-time inference.\n2+ years of experience with cloud platforms (GCP preferred; AWS or Azure acceptable).\n2+ years working with streaming platforms like Kafka or equivalent.\n2+ years of experience with databases (Postgres or similar relational systems).\n2+ years of experience with CI/CD tools (GitHub Actions, Jenkins, Argo CD, etc.).\n2+ years of hands-on experience with Infrastructure as Code tools (Terraform preferred; Pulumi or CDK acceptable).\n2+ years managing containerized workloads using Kubernetes (GKE, EKS, or AKS) — deploying services, configuring autoscaling, and managing resource limits.\nSolid understanding of cloud networking fundamentals: VPCs, subnets, firewall rules, private connectivity, and DNS resolution in GCP or AWS.\nExperience designing IAM roles, service accounts, and secrets management workflows to enforce least-privilege access across data services.\nFamiliarity with infrastructure monitoring and alerting tools (Cloud Monitoring, Prometheus/Grafana, or equivalent).\nPreferred Qualifications\nDirect, hands-on experience with Google Cloud Platform, especially BigQuery, Dataflow, GKE, Composer and Vertex AI.\nKnowledge of Kubernetes concepts and experience running data services or pipelines on GKE.\nStrong understanding of distributed systems, microservice patterns, and data-centric system design.\nExperience using Vertex AI, Kubeflow, or other ML orchestration platforms for model training and serving.\nKnowledge of GenAI pipelines, LLM prompt workflows, and agent orchestration frameworks (e.g., LangChain, transformers).\nExperience deploying Python-based ML/NLP services into microservice ecosystems using REST, gRPC, or sidecar architectures.\nDomain experience in healthcare, claim adjudication, or Rx data processing.\nExperience with Terraform modules, workspaces, and remote state backends for managing multi-environment GCP infrastructure.\nFamiliarity with GCP Shared VPC, VPC Service Controls, or private Google Access configurations for secure data platform networking.\nExposure to FinOps practices — cloud cost attribution, showback/chargeback models, and resource tagging strategies.\nExperience with GitOps workflows using Argo CD or Flux for managing infrastructure and application delivery.\nEducation\nBachelor's degree in Computer Science, Data Engineering, Information Systems, or equivalent experience (High School Diploma + 4 years of relevant experience acceptable).","description_format":"text","description_chars":6323,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Continuous learning"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Custom Software Development","IT Staffing & Staff Augmentation","IT Training & Certification"],"lifecycle":[{"event":"open","at":"2026-10-09T17:09:00Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":1,"expected_fill_days":22,"reasons":["seen:1","velocity","win:early"],"computed_at":"2026-10-10T05:45:15Z"},"pay":null,"html_url":"https://alion.io/job/intraedge-data-engineer-aiml-engineer","json_url":"https://alion.io/job/intraedge-data-engineer-aiml-engineer.json","meta":{"generated_at":"2026-10-12T00:53:03Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":740,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-13T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":62138},"rest":"https://alion.io/mcp/rest/get_company?id=62138"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fintraedge-data-engineer-aiml-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fintraedge-data-engineer-aiml-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fintraedge-data-engineer-aiml-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/intraedge-data-engineer-aiml-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fintraedge-data-engineer-aiml-engineer"}]}