Senior Network Automation Engineer - AI​/ML

Job Title:

Senior Network Automation Engineer - AI/ML, AIOps & Network Operations

Location:

Jersey City, NJ / Charlotte, NC / Chandler, AZ Duration:
Contract - 12 months Pay Range: NJ,Jersey City- $104.62 (Pay Rate: $73.67)
-Preferred location NC, Charlotte -$99.73 (Pay Rate: $70.23)-preferred location AZ, Chandler- $99.73 (Pay Rate: $70.23) Job  About BCforward BCforward is a leading global IT consulting and workforce solutions firm providing services and support to Fortune 500 and government clients. Founded in 1998, BCforward has grown with our customers needs into a full-service business solutions provider. With delivery centers and offices across North America and India, we take pride in building long-term relationships and delivering excellence through innovation, collaboration, and integrity.

Job Description We are seeking a Senior Network Automation Engineer - AI/ML, AIOps & Network Operations to join our dynamic team. The ideal candidate will have strong experience in Python-based backend development, network automation, telemetry integration, and applied AI/ML for operations and a proven ability to deliver safe, reliable automation and AI-assisted troubleshooting in production environments. Responsibilities:
Design and develop network automation services for event correlation, intelligent troubleshooting, and automated remediation. Build automation that supports self-healing use cases with automated checks, safe remediation actions, and guided recovery steps. Develop backend automation services using Python and Django with supporting data stores such as Redis for state and caching. Integrate automation with monitoring, telemetry, and alerting systems to consume events and metrics in near real time.

Partner with Network Operations to identify repeatable operational patterns suitable for automation. Collaborate with Monitoring and Telemetry engineers to ensure automation logic is driven by reliable data signals. Implement guardrails, validation, and rollback logic to ensure safe production usage. Contribute to testing, versioning, deployment, and operational support for automation services. Provide production support and troubleshooting for automation services. Document designs, runbooks, and usage guidelines for Operations teams.

Design and product ionize ML solutions for anomaly detection, event correlation, incident classification, root-cause analysis, forecasting, and predictive maintenance. Engineer and curate telemetry datasets, perform feature engineering, labeling, data quality validation, and model-ready transformations across metrics, logs, events, traces, and topology. Develop AI-assisted troubleshooting using LLMs, RAG, embeddings, and enterprise knowledge sources with human oversight and deterministic controls. Build and maintain MLOps pipelines for experiment tracking, validation, versioning, deployment, monitoring, retraining, and rollback.

Evaluate models using precision, recall, false-positive reduction, resolution accuracy, latency, reliability, and operational adoption. Implement responsible AI controls including explainability, privacy, security, bias assessment, auditability, access control, drift monitoring, and safe fallback behavior. Create APIs and reusable services that integrate AI/ML inference with event management, observability, orchestration, and ITSM platforms. Required Skills &

Qualifications:

Strong software development experience in Python, including REST APIs, message queues, or workflow engines. Experience building backend services using Django or similar frameworks. Hands-on experience with Redis or equivalent in-memory data stores. Solid understanding of enterprise networking including routing, switching, wireless, and SD-WAN concepts. Experience integrating automation with monitoring, alerting, or telemetry systems. Ability to design automation for reliability and safety in production environments.

Experience operating in high availability, failure-sensitive environments. Strong communication and collaboration with engineering and operations teams.

Education:

Bachelor's or Master's in Computer Science, Engineering, or related field.

Experience:

8-12 years in network engineering, operations, automation, telemetry, monitoring, data engineering, or applied analytics with production AI/ML delivery. Preferred

Skills:

Experience with event correlation, rule-based automation, or decision workflows. Familiarity with observability data, including metrics, logs, and events, as automation…