Pre-screened and vetted.
Mid-level Software Development Engineer specializing in backend, cloud, and microservices
“Accenture engineer with hands-on experience taking an NLP sentiment analysis system from prototype to production, emphasizing robustness to noisy data, scalability, and observability (dashboards for latency/error/throughput). Also supports customer-facing teams with demos and PoCs, translating client requirements into secure, scalable architectures and troubleshooting LLM/agent workflows via logs and step-level traces.”
Mid-level Full-Stack Software Engineer specializing in Java/Spring, React, and AWS
“Backend/data engineer with production experience across event-driven Python ingestion services on AWS (EventBridge/SQS/MongoDB), serverless APIs (Lambda/API Gateway), and analytics ETL (Glue → Redshift). Has modernized legacy reporting into Node.js/React systems and demonstrated measurable SQL performance wins (minutes to seconds) plus strong incident ownership with validation, DLQs, and alerting.”
Mid-level Data Scientist & AI Engineer specializing in NLP, LLMs, and predictive analytics
“AI Engineer with production experience building an LLM-powered conversational scheduling assistant (rules-based + OpenAI GPT agents) and improving responsiveness by ~40% through architecture optimization. Strong in orchestration (Airflow), containerized deployments, and data quality (Great Expectations/PySpark), with prior work automating population health reporting pipelines (Azure Data Factory → Snowflake) and delivering insights via Tableau to non-technical stakeholders.”
Junior Data Scientist specializing in generative AI and RAG systems
“Data scientist at Guardian Airwaves building a RAG-powered quiz generator using Grok AI, with hands-on experience solving hard document-ingestion problems (PDFs with images/tables) via unstructured.io and LlamaIndex. Has deployed production systems on AWS EC2 and brings a pragmatic approach to agent reliability (human-in-the-loop, LLM-based eval, latency/cost metrics) while effectively translating RAG concepts to non-technical stakeholders.”
Junior Machine Learning Engineer specializing in NLP, data pipelines, and LLM workflows
“Built and shipped a production LLM-powered decision system that replaced a slow, inconsistent manual review process by turning messy text into structured, auditable outputs behind an API. Demonstrates strong end-to-end ownership of reliability and operations (schema validation, retries/fallbacks, latency/cost controls, monitoring for drift) and a disciplined approach to evaluation and regression testing. Experienced collaborating with non-technical reviewers to define success criteria and deliver interpretable outputs that get adopted.”
Director-level Operations & HR Talent Strategy leader specializing in performance metrics and L&D
“Operations Manager leading a 10-person BA team and owning operations execution across three lines of business, with additional ownership of OKRs tied to talent development (IDPs), value metrics, and recognition programs. Designed an onboarding framework aligned to company strategy and OKRs that improved retention, ramp-up, and engagement, and built healthcare college partnerships to strengthen hiring and internship pipelines while supporting cross-functional enterprise system implementations (policy admin, finance/HR, billing, call centers).”
Intern Marketing Analytics professional specializing in GA4, experimentation, and BI reporting
“Outbound-focused business development profile spanning a family-owned construction materials business in India and an early-stage startup (Jetvoy) targeting Web3/travel partners. Built ICP, messaging, and a spreadsheet-based CRM from scratch, ran multi-channel campaigns (email/LinkedIn/calls), and leveraged tools like Sales Navigator, Apollo, HubSpot/Sheets, Zapier-style automations, and ChatGPT to improve reply/meeting rates through personalization.”
Mid-level Full-Stack Engineer specializing in data automation, cloud & AI
“JavaScript engineer who effectively "maintains" an internal open-source-style React/Node.js shared library used by multiple teams—owning API stability, semantic versioning, CI/testing, logging, and documentation. Demonstrates strong cross-team debugging and change-management skills (schema-driven refactors, feature flags, validation layers) to ship new features without breaking existing workflows, plus a profiling/benchmarking-driven approach to performance.”
Mid-level Customer Success Engineer specializing in AI analytics and cloud deployments
“Customer Success Engineer focused on secure customer integrations for web/AI analytics solutions, frequently aligning retail/business teams with security requirements. Has hands-on experience troubleshooting and hardening API-based integrations in AWS (IAM least privilege, VPC/private subnet patterns, CloudWatch/CloudTrail) and delivering repeatable containerized deployments via Bitbucket CI/CD.”
Mid-level Marketing Analytics & Growth Specialist in performance marketing
“Paid media specialist with nonprofit/fundraising experience at Keelworks Foundation, running high-spend acquisition across Google, Meta, and LinkedIn (and familiar with TikTok). Uses CRM-driven funnel segmentation and disciplined A/B testing across ads, landing pages, and email flows; has recovered stalled performance and delivered ~10% donation growth while tracking deep donor-quality KPIs (lead-to-donor, retention, avg gift).”
“Game QA professional experienced in live production pipelines with daily builds and sprint cadence, emphasizing LKG-based verification/regression, smoke/BVT stability checks, and disciplined backlog closure. Known for isolating low-repro gameplay/system defects using video evidence and logs, and for streamlining team workflows through standardized JIRA/Azure DevOps templates and data-driven quality feedback to designers/engineers.”
Mid-level Software Engineer specializing in full-stack development and backend APIs
“Backend engineer who has designed and evolved high-traffic event/activity management systems using Node/Express and PostgreSQL, prioritizing scalability and reliability with a layered architecture. Has led zero-downtime refactors/migrations using parallel runs, dual writes, and rigorous validation/monitoring, and brings a security-focused API approach (JWT, RBAC/ABAC, rate limiting, DB-enforced tenant/RLS filters).”
Senior Full-Stack Engineer specializing in scalable React/Next.js platforms
“Backend/data engineer with strong production experience across Python microservices (FastAPI) and AWS serverless/data platforms (Lambda, API Gateway, Glue, Redshift). Demonstrates reliability and incident ownership (rate limits, retries/circuit breakers, monitoring) and has delivered measurable SQL performance gains (12–15s to <800ms, ~60% CPU reduction). Seeking fully remote work and not open to relocation/onsite meetings.”
Junior Full-Stack Software Engineer specializing in web apps, data workflows, and AI integrations
“Backend engineer with experience stabilizing data processing/analytics pipelines and refactoring brittle backend APIs. Has hands-on FastAPI work emphasizing strong validation (Pydantic), clear layering, and secure JWT-based auth with role/row-level controls, plus pragmatic migration tactics like parallel runs to protect data integrity.”
Mid-level AI/ML Engineer & Data Scientist specializing in NLP and Generative AI
“Built and deployed an agentic RAG platform at Centene Health to support healthcare claims and complaints workflows (Q&A for claims agents, executive complaint summarization, and compliance triage/classification). Experienced in LangChain/LangGraph orchestration, production deployment on AWS with FastAPI/Docker/Kubernetes, and implementing HIPAA-compliant guardrails to reduce hallucinations and ensure explainable outputs.”
Senior Software Developer specializing in Unity VR and mobile apps
“Unity/VR developer who shipped a Meta Quest wireless conversion of a previously wired VR product, owning research, network troubleshooting (2.4 vs 5 GHz), performance tuning, and reworking hand tracking. Also built a British Airways cabin crew training application largely solo and deployed it across iOS, Android, PC, WebGL, and Web Player with platform-specific optimization strategies.”
Mid-level Machine Learning & AI Engineer specializing in Generative AI, NLP, and MLOps
“Built and deployed production LLM systems for summarizing sensitive legal and financial documents, emphasizing GDPR-aligned privacy controls and scalable hybrid cloud architecture. Experienced with Kubernetes/Airflow orchestration and rigorous testing/monitoring practices, and has delivered measurable business impact (18% conversion lift) by translating AI outputs for non-technical marketing stakeholders.”
Intern Software Engineer specializing in backend systems and Generative AI
“Built and deployed a scalable, production-ready LLM knowledge assistant using a RAG architecture (LangChain + vector store/FAISS) to replace keyword search for internal documents. Demonstrates hands-on expertise in hallucination reduction and retrieval quality improvements through semantic chunking, similarity tuning, prompt design, and human-in-the-loop validation, plus strong stakeholder communication via demos and visual explanations.”
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic systems
“Built a production "Mini RAG Assistant" for internal document Q&A, focusing on grounded answers (anti-hallucination), retrieval quality, and latency/cost optimization. Uses LangChain/LangGraph for orchestration and applies a metrics-driven evaluation loop (including reranking and semantic chunking improvements) while collaborating closely with product stakeholders.”
“Built and deployed a production LLM-powered RAG knowledge system to unify operational/policy information across PDFs, wikis, and databases, emphasizing auditability and low-latency/cost performance. Improved answer relevance at scale by moving from pure vector search to hybrid retrieval with metadata filtering and reranking, and partnered closely with healthcare operations/compliance to define acceptance criteria and human-in-the-loop guardrails.”
Mid-level GenAI Engineer specializing in RAG, LLM agents, and enterprise automation
“Accenture engineer who built and shipped a production RAG-based automation/chatbot for SAP incident triage and troubleshooting, embedding thousands of runbooks/logs/tickets into a semantic search pipeline and integrating it into Teams/Slack. Reported major productivity gains (30–60% time reduction), >90% validated answer accuracy, and sub-2-second responses, with strong orchestration (Airflow/Prefect/LangGraph) and reliability practices (guardrails, testing, monitoring).”
“At Liberty Mutual, built a production underwriting decision assistant combining LLM reasoning with quantitative models and strong auditability. Implemented a claims-based response verification pipeline that cut hallucinations from 18% to 3% and materially improved user trust/validation scores. Experienced orchestrating ML/LLM workflows end-to-end with Airflow, Kubeflow Pipelines, and Jenkins, including SLA-focused pipeline hardening.”
Mid-level GenAI/Data Engineer specializing in LLMs, RAG systems, and fraud detection
“ML/NLP engineer with banking domain experience who built a GenAI-powered fraud detection and risk intelligence system at Origin Bank, combining RAG (LangChain + FAISS), fine-tuned BERT NER, and GPT-4/Sentence-BERT embeddings. Delivered measurable impact (25% higher fraud detection accuracy, 40% less manual review) and emphasizes production-grade pipelines on AWS SageMaker/Airflow with strong data validation and scalable PySpark processing.”