AI Sr. Engineer LLMOps & MLOps (1483466)

Job Title: AI Sr. Engineer LLMOps & MLOps (1483466)

Location: Remote

Duration: Direct Hire

Pay Range: $150,000 - $170,000 salary

Job ID: 372252

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 an AI Sr. Engineer focused on LLMOps & MLOps to join our Transformation Office. The ideal candidate will have strong experience in multi-cloud AI/ML operations across AWS and Azure and a proven ability to build automated, secure, and scalable production infrastructure for LLM applications, RAG pipelines, and traditional ML models.

Responsibilities:

• Build and maintain automated CI/CD and Continuous Training pipelines across AWS (SageMaker, Bedrock) and Azure (AI Studio).


• Design and implement LLMOps frameworks for Retrieval-Augmented Generation, including vector database management (OpenSearch, Pinecone, Azure AI Search) and semantic index optimization.


• Create secure data ingestion and connectivity from legacy systems (Mainframes, SQL Server, on-prem databases) into cloud-native MLOps workflows.


• Implement automated model evaluation for LLMs and ML, including LLM-as-a-judge, ROUGE, and METEOR, to validate performance pre-deployment.


• Deploy observability and monitoring for model drift, hallucination detection, latency, and token consumption to manage quality and cost.


• Manage Infrastructure as Code with Terraform or CloudFormation to ensure reproducible, secure, and privacy-first cloud environments.


• Integrate with advanced analytics platforms such as Palantir, Databricks, or Snowflake for reliable data flow between analytical ontologies and production models.


• Partner with IT and Security to navigate IAM roles, VPC peering, and firewall configurations to enable rapid transformation.


• Engineer scalable inference using containerization (Docker, Kubernetes) and serverless architectures for high-throughput and low-latency serving.


• Establish prompt and model versioning (PromptOps), model weight tracking, and data snapshotting for auditability and rollback.


• Support data science by automating feature stores, feature engineering pipelines, and productionizing notebooks into reliable microservices.


• Implement security and compliance guardrails, including automated scanning and content safety to mitigate prompt injection and data leakage.

Required Skills & Qualifications:

• Proficiency in AWS (SageMaker, Bedrock) and Azure (AI Studio) services for ML and LLM workloads.


• Hands-on experience with CI/CD and CT pipelines for ML, including orchestration and automation.


• Expertise with vector databases and RAG patterns, including OpenSearch, Pinecone, or Azure AI Search.


• Strong skills in Infrastructure as Code using Terraform or CloudFormation and configuration management.


• Experience building secure data pipelines from legacy systems to cloud platforms, including SQL Server and mainframe sources.


• Knowledge of LLM and ML evaluation methodologies such as LLM-as-a-judge, ROUGE, and METEOR.


• Competence with observability stacks for ML/LLM monitoring, drift detection, latency, and cost metrics.


• Containerization and orchestration experience with Docker and Kubernetes, plus serverless inference patterns.


• Familiarity with data platforms such as Palantir, Databricks, or Snowflake for production data integration.


• Understanding of IAM, networking, and security controls, including VPC peering and firewall policies.


• Experience with prompt and model version control and reproducible ML workflows.


• Experience level: Senior engineer with demonstrated ownership of production AI/ML systems.

Preferred Skills:

• Experience with feature stores and automated feature engineering pipelines.


• Experience implementing content safety and guardrails (e.g., Bedrock Guardrails, Azure Content Safety).

Why BCforward?

At BCforward, we believe in advancing lives and careers. When you join our team, you gain access to:

• Competitive compensation and benefits


• Opportunities for growth with global clients


• A supportive, inclusive culture that values innovation and people


• Exposure to cutting-edge technologies and projects

About Our Commitment

BCforward is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or veteran status.

Interested? Apply Now!

If this sounds like the right opportunity for you, please apply with your most recent resume. Please include your salary criteria and current location in your resume.