Accellor

Software Engineer

• Design, develop, and maintain advanced conversational experiences using Microsoft Copilot Studio / Power Virtual Agents.
• Build complex topics, actions, workflows, variables, plugins, and custom extensions in Copilot Studio.
• Architect end-to-end Copilot-powered solutions using Power Platform (Power Apps, Power Automate, Dataverse, AI Builder).
• Integrate Copilot solutions with Azure services, API Management, external systems, and enterprise data sources.
• Implement Human-in-the-Loop (HITL), escalation paths, fallback logic, and advanced conversation orchestration.
• Optimize bot performance using analytics, telemetry, usage data, and conversational metrics.
• Develop and review custom connectors, Azure Functions, Logic Apps, and integration frameworks.

Senior Developer – Microsoft Copilot Studio

Sales

• Design, build, and deploy Salesforce Agentforce solutions that automate customer and employee interactions.
• Configure Salesforce Service Cloud to deliver AI-powered case management, self-service, and intelligent support experiences.
• Build AI agents using Agentforce, including prompts, topics, actions, orchestration, and conversational workflows.
• Integrate Agentforce with Salesforce CRM, Knowledge, Flows, Data Cloud, and enterprise applications.
• Configure Salesforce Trust Layer, security controls, and data grounding to ensure secure and responsible AI experiences.
• Develop scalable Salesforce solutions using Apex, Lightning Web Components (LWC), Salesforce Flows, Platform Events, and APIs.
• Partner with solution architects and client stakeholders to identify high-value AI use cases and translate business requirements into scalable technical solutions.
• Participate in architecture reviews, technical design sessions, code reviews, and solution planning.
• Support testing, deployment, release management, and production optimization.
• Champion Salesforce best practices while contributing to reusable assets and delivery standards across client engagements.

Salesforce Engineer

Backend Engineer

• Code in a full-stack arena. React.js, Next.js, TypeScript / JavaScript. SPA architecture + GraphQL + Kotlin experience is a plus.
• Drive the design and implementation of solutions and product features, as well as support the live operation at scale of user-facing critical Web and Mobile flows.
• Test automation, monitoring and alerting experience is desired.
• Participate in the prioritization process to bring hidden technical needs to the roadmap.
• Translate business requirements into technical ones with very strong communication skills.
• Lead the team to build scalable, easy-to-maintain software to support millions of users and transactions.

Senior Frontend Engineer, React, Java Spring

DevOps Engineer

• Work directly with customer engineering, product, business, and domain teams to understand workflows, technical constraints, and high-value AI opportunities.
• Translate ambiguous customer problems into clear technical plans, success criteria, and delivery milestones.
• Identify where models can deliver measurable value in real production workflows.
• Design AI-powered systems that integrate models with customer data, tools, APIs, applications, and security controls.
• Define practical architecture for model usage, retrieval, context management, tool calling, orchestration, evaluation, monitoring, and production reliability.
• Build prototypes, production applications, APIs, integrations, internal tools, and workflow automation using models.
• Work closely with customer engineering teams to connect AI systems into existing enterprise platforms, data sources, identity systems, and business processes.
• Own the path from prototype to production, including testing, rollout planning, observability, reliability, and operational readiness.
• Ensure deployed systems are secure, usable, measurable, and aligned with customer success criteria.
• Define evaluation methods to measure model quality, grounding, accuracy, latency, cost, safety, and workflow impact.
• Capture learnings from real customer deployments and share actionable feedback with Product, Research, Engineering, Safety, and GTM teams.

Forward Deployment Engineer – Frontier AI Deployments

• Design and evolve large-scale AI systems that support ChatGPT, OpenAI API, Codex, agentic workflows, multimodal models, and research workloads.
• Define architecture across inference runtime, model serving, request routing, batching, KV-cache handling, GPU scheduling, distributed execution, observability, release gates, and production rollout.
• Own technical trade-offs across latency, throughput, reliability, correctness, safety, scalability, cost, and infrastructure efficiency.
• Architect high-throughput, low-latency inference systems across large-scale GPU clusters.
• Work across inference engines, serving layers, scheduling systems, caching, streaming, deployment pipelines, and runtime optimization.
• Partner with engineering teams to improve model-serving efficiency, tail latency, GPU utilization, memory efficiency, correctness under load, and cost per request.
• Guide architecture decisions involving PyTorch, JAX, Triton, vLLM-style serving, CUDA/Triton kernels, distributed inference, tensor parallelism, pipeline parallelism, model sharding, and long-context serving.
• Analyze and improve performance across GPU kernels, memory movement, collective communication, orchestration, and runtime scheduling.
• Guide engineering decisions involving CUDA, Triton, NCCL/RCCL, GPU profiling, memory pressure, compute utilization, tensor layouts, interconnect behavior, and distributed execution.
• Identify system-level bottlenecks across compute, memory, networking, scheduling, model execution, and data movement.
• Design and guide context engineering frameworks that determine what information should be passed to the model, how it should be structured, how much context should be used, and how context quality should be measured.
• Own architecture patterns for prompt structure, dynamic context assembly, retrieval-augmented generation, long-context management, conversation memory, tool context, agent state, multimodal context, source grounding, permission-aware retrieval, context compression, and context auditability.
• Ensure AI systems use the right context, from the right source, with the right permissions, at the right cost, and with measurable quality.
• Design and build cost optimization frameworks for large-scale LLM and GenAI workloads.
• Create architecture patterns that reduce unnecessary token usage, redundant retrieval, repeated model calls, inefficient inference paths, and avoidable infrastructure spend.
• Drive model routing, token budgeting, prompt compression, context pruning, semantic caching, response caching, batch inference, async execution, fallback strategies, and cost telemetry across AI workflows.
• Ensure cost optimization does not compromise quality, safety, grounding, reliability, or user experience.
• Collaborate with research and training infrastructure teams to support large-scale model training and post-training workflows.
• Contribute to architecture around distributed training, checkpointing, orchestration, fault tolerance, observability, data movement, evaluation infrastructure, and experiment velocity.
• Support frontier model workflows across pre-training, post-training, reinforcement learning, agent training, evaluation harnesses, and large-scale experiment execution.
• Architect validation and release systems that ensure model updates, inference engine changes, runtime images, prompt changes, context changes, and platform releases are correct, safe, performant, and regression-free.
• Define release gates across correctness, numerical stability, latency, throughput, token usage, cost regression, context quality, retrieval quality, safety behavior, reliability, and model output quality.
• Ensure platform optimizations do not reduce safety, grounding, quality, or user trust.
• Design systems that make AI infrastructure observable, debuggable, reliable, and operationally safe.
• Define telemetry, tracing, dashboards, alerts, logs, profiling views, runbooks, SLOs, and post-incident learning loops.
• Provide visibility into prompts, context payloads, retrieved sources, token consumption, model selection, cache behavior, inference latency, GPU utilization, evaluation scores, safety events, cost, and failures.
• Turn production issues into stronger platform abstractions, safer rollout mechanisms, better automation, and more reliable infrastructure.
• Support architecture for AI agents, tool use, memory, function calling, multimodal interaction, long-running workflows, and internal or external agent deployment.
• Work across agent harnesses, evaluation pipelines, workflow orchestration, safety controls, state management, tool execution, memory systems, and product-facing runtime constraints.
• Ensure agentic and multimodal systems are reliable, observable, secure, cost-aware, and safe under real workloads.
• Work closely with Research, Inference, Runtime, Infrastructure, Product, Safety, Security, Technical Success, and Deployment teams.
• Act as a senior technical authority who can cut across layers, resolve ambiguity, identify systemic risks, and drive architecture decisions.
• Mentor engineers and technical leads on distributed systems, performance engineering, context engineering, cost optimization, production readiness, AI platform design, and architecture trade-offs.
• Represent architecture decisions through design docs, RFCs, diagrams, technical reviews, operational plans, and leadership-level summaries.

AI Systems & Platform Internals – Technical Architect

• Own the architecture for backend services and platforms — microservices boundaries, API contracts, data models, and inter-service communication patterns.
• Make and document key technical decisions (build vs. buy, sync vs. async, consistency vs. availability trade-offs) and align teams around them.
• Set and enforce engineering standards: code quality, testing strategy, observability, and operational readiness.
• Directly manage, mentor, and grow a team of backend engineers, including running 1:1s, setting goals, giving feedback, and supporting career development.
• Plan, distribute, and track work across the team — breaking down epics, sequencing delivery, and removing blockers so the team ships predictably.
• Mentor junior and mid-level engineers through pairing, code review, and design coaching, raising the bar for the whole team rather than being the single point of delivery.
• Partner with product, architecture, and other engineering leads to translate business goals into technical roadmaps and realistic commitments.
• Lead by example with hands-on contribution to high-impact and complex parts of the codebase.
• Design and operate microservices: service decomposition, API design (REST/gRPC/GraphQL), versioning, and backward compatibility.
• Build event-driven and asynchronous workflows using message queues and streaming platforms (Kafka, RabbitMQ, SQS, or similar).
• Design data persistence and caching strategies across relational and NoSQL stores, with appropriate use of caching layers (Redis/Memcached) for performance and scale.
• Ensure systems are designed for scale, resilience, and graceful degradation — load balancing, rate limiting, retries, circuit breakers, and idempotency.
• Drive observability across services: structured logging, metrics, distributed tracing, and actionable alerting.
• Enforce backend security best practices: authentication/authorization (OAuth2, OIDC, JWT), least-privilege access, secrets management, and secure handling of data in transit and at rest.
• Own production quality — on-call leadership, incident response, root-cause analysis, and follow-through on remediation.
• Collaborate with DevOps and platform teams on CI/CD, containerization, and deployment strategy for backend services.
• Recommend and implement standards for code organization, service ownership, and technical governance across teams.

Backend Tech Lead

Salesforce Developer

• Lead the design and execution of Salesforce solutions for a recently launched project
• Ensure robust, scalable solutions following Salesforce best practices
• Collaborate with business stakeholders to translate requirements into practical solutions
• Manage the full implementation of Salesforce solutions across various platforms
• Continuously evaluate project progress and suggest improvements

Salesforce Solutions Architect

Technical Program Manager

• Manage the Portfolio: Oversee the end-to-end lifecycle of multiple concurrent projects (e.g., BOPIS, Ship-from-Store, Endless Aisle, POS integrations) from concept to launch.
• Technical Alignment: Work closely with Solution Architects and Engineering Leads to ensure technical designs are scalable and align with business goals.
• Dependency Management: Identify and resolve critical path dependencies between frontend teams (Web/Mobile), backend services (OMS/ERP), and third-party logistics providers.
• Stakeholder Reporting: Provide clear, data-driven status reporting to VP-level executives regarding program health, risks, and milestone achievements.
• Agile Governance: Facilitate Sprint Planning, Scrum of Scrums, and Quarterly Planning (PI Planning) sessions to prioritize the backlog effectively.

• Assess current-state business processes, applications, and technology capabilities
• Identify capability gaps and define future-state operating models
• Develop and maintain a multi-year transformation roadmap
• Build program charters, governance frameworks, and success metrics
• Support business case development, ROI analysis, and total cost of ownership (TCO) planning
• Lead large-scale enterprise transformation programs across business and technology teams
• Manage multiple workstreams, dependencies, milestones, and risks
• Drive Agile and SAFe-based program execution across distributed teams
• Establish delivery governance, reporting frameworks, and quality standards
• Track progress against program objectives and business outcomes
• Partner with senior business and technology leaders to align priorities and expectations
• Facilitate steering committee meetings and executive decision-making forums
• Develop executive-level communications, dashboards, and status reporting
• Define and monitor transformation KPIs and value realization metrics
• Support vendor strategy, RFP development, evaluation, and selection activities
• Manage system integrators and third-party implementation partners
• Monitor vendor performance, contractual commitments, and service-level agreements
• Ensure successful execution of statements of work and delivery commitments

Procurement

• - Gather, analyze, and document business requirements related to procurement and sourcing processes.
• - Serve as a functional SME for Oracle Fusion Procurement Cloud modules.
• - Configure and support Oracle Fusion Procurement functionalities including:
• - Self-Service Procurement (SSP)
• - Purchasing
• - Supplier Qualification
• - Supplier Portal
• - Sourcing
• - Procurement Contracts
• - Supplier Management
• - Translate business requirements into functional specifications and solution designs.
• - Conduct fit-gap analysis and recommend best-practice Oracle Fusion solutions.
• - Collaborate with technical teams for integrations, customizations, reports, and data conversions.
• - Support procurement process optimization and digital transformation initiatives.
• - Facilitate UAT sessions, end-user training, and deployment activities.
• - Troubleshoot production issues and provide ongoing application support.
• - Develop and maintain functional design documents, process flows, and test scripts.
• - Work closely with cross-functional teams including Finance, Supply Chain, Inventory, and ERP support teams.
• - Participate in Oracle Fusion upgrades, patch assessments, and release management activities.
• - Ensure compliance with procurement policies, governance standards, and audit requirements.

Senior Developer – Microsoft Copilot Studio

Salesforce Engineer

Senior Frontend Engineer, React, Java Spring

Forward Deployment Engineer – Frontier AI Deployments

AI Systems & Platform Internals – Technical Architect

Backend Tech Lead

Salesforce Solutions Architect

Technical Program Manager

Technical Program Manager

Senior Procurement Analyst