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Vetted AWS Step Functions Professionals
Pre-screened and vetted.
Mid-level Software Engineer specializing in full-stack and cloud-native systems
Mid-level Backend Software Engineer specializing in AWS microservices and REST APIs
Mid-level Data Engineer specializing in cloud data pipelines and analytics platforms
Director-level engineering leader specializing in FinTech platforms and AI-native systems
Intern Software Engineer specializing in cloud, backend systems, and LLM-powered tooling
Mid-level AI/ML Engineer specializing in GenAI, RAG, and cloud-native ML platforms
Mid-level AI/ML Engineer specializing in NLP, RAG, and agentic AI
Mid-level Full-Stack Developer specializing in React, Node.js, and cloud-native AWS systems
Senior DevOps Engineer / AWS Solutions Architect specializing in Kubernetes and DevSecOps
Senior AI/ML Engineer specializing in GenAI, LLMs, NLP, and MLOps
Omolara Okubanjo
Senior DevOps/DevSecOps Engineer specializing in AWS & Azure cloud infrastructure
“Infrastructure/DevOps-focused engineer working across Linux-based enterprise platforms that include IBM Power/AIX in a broader OpenShift/Kubernetes and cloud ecosystem. Built Azure DevOps CI/CD for containerized deployments and resolved a production deployment failure by tracing ImagePullBackOff to outdated registry credentials in Kubernetes secrets. Uses Terraform (with modular structure) plus Ansible to provision and standardize production environments with pipeline-based validation.”
Tauhid Arah
Senior DevOps Engineer specializing in AWS cloud platform engineering and Kubernetes
“Cloud-focused DevOps/Infrastructure engineer with hands-on AWS high availability, migration cutovers, and production automation. Built Jenkins-based CI/CD pipelines (Git, SonarQube, Artifactory) and manages Terraform IaC with S3/DynamoDB remote state, PR-based reviews, and staged environment promotion; targets $160k base. No direct IBM Power/AIX/PowerHA experience.”
David Kidwell
Senior AI/ML Data Scientist specializing in NLP, computer vision, and MLOps
“Applied LLMs and a graph-RAG architecture in Neo4j to automate an accounting firm's cross-checking of transactional books against tax regulations, indexing 1,000+ pages into a knowledge graph with vector search. Combines agentic LLM workflows with classical NER (Hugging Face/NLTK) and validates using expert-labeled held-out data plus precision/recall and measured accountant time savings after deployment.”
Intern Software Engineer specializing in cloud data platforms and full-stack systems
Intern-level Software Engineer specializing in backend systems and applied AI
Senior Full-Stack Engineer specializing in Python, cloud-native systems, and LLM applications
Senior Software Engineer specializing in cloud-native backend, ETL, and AI/ML on AWS
Mid-level Data Engineer specializing in AWS lakehouse and Spark pipelines
Senior Data Engineer specializing in Cloud Data Platforms and Generative AI
Senior Full-Stack Developer specializing in Python, AWS, and data/ETL systems
Sasi Katamneni
Mid-level Data Scientist / AI-ML Engineer specializing in Generative AI and LLM applications
“Built a production GenAI-powered analytics assistant to reduce reliance on data analysts by enabling natural-language Q&A over Databricks/Power BI dashboards, backed by vector search (Pinecone/Milvus) and a Neo4j knowledge graph, including multimodal support via OpenAI Vision. Demonstrates strong real-world LLM reliability engineering with strict RAG, LangGraph multi-step verification, and Guardrails/custom validators, plus broad orchestration and production monitoring experience (Airflow, ADF, Step Functions, Kubernetes, Prometheus/CloudWatch).”
Sunil Chinthaparthi
Mid-level Python Developer specializing in AWS microservices and cloud automation
“Backend engineer focused on Python/FastAPI microservices running on Kubernetes (AWS EKS) with strong GitOps/CI/CD ownership (GitHub Actions + ArgoCD). Demonstrated measurable performance wins (p95 latency cut from >1s to <200ms) and production reliability work across Kafka/Redis streaming and cloud-to-on-prem migrations (RDS/S3 to Postgres/MinIO) using parallel validation and checksum-based consistency checks.”
Swathi Sankaran
Senior Python Full-Stack Developer specializing in cloud, data engineering, and ML/GenAI
“Backend/data engineer with hands-on production experience building FastAPI services on AWS and implementing strong reliability/observability (CloudWatch, ELK, correlation IDs, alarms). Has delivered serverless + container solutions with IaC (CloudFormation/Terraform) and Jenkins CI/CD, and built AWS Glue/PySpark pipelines into S3/Redshift with schema-evolution and data-quality safeguards; demonstrated large-scale SQL tuning (45 min to 3 min on a 500M-row workload).”