Abinash Behera
Director Product Engineering @Acxiom Salesforce Practice
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WORK HISTORY
Director Product Engineering @Acxiom Salesforce Practice
Mississauga, ON, CA
Defining and driving a unified vision for product quality and innovation; formulating & implementing comprehensive Quality Engineering and Test Automation strategies aligned with organizational goals and influencing ExecutiveLeadership on strategic decisions related to product quality, engineering processes, and automationLeading initiatives to embed quality into every stage of the product lifecycle right from design and development to release and support by implementing scalable QA frameworks, test strategies, and QA policies for all product linesMonitoring development of automated testing solutions, Continuous Integration (CI) pipelines,and Performance Testing frameworks while promoting a Test-Driven Development (TDD) and Behavior-Driven Development (BDD) culture across teams; evaluating and implementing modern toolsets and technologies to drive automation and reduce manual effortIdentifying early risks and implementing mitigation plans to maintain product reliability and customer trust while ensuring compliance with industry standards,(e.g, ISO, GDPR, and more)Defining, measuring, and analyzing key quality metrics such as defect rates, test coverage, andautomation ROI; presenting quality reports and product health dashboards to senior leadershipPartnered closely with Product Management, Engineering, DevOps, Customer Support, andSales to align quality objectives; understanding user pain points and ensuring product reliability andusability; managing vendor relationships and assess third-party tools or platforms for integration and compliancePlanning and managing budgets for QA tools, training, and staffing; allocating resources basis project priorities, risk exposure, and product release timelines to maximize ROIMentoring, and leading high-performing team comprising 36 employees, spread across the US, Canada, Panama, and India by defining team goals, conducting performance evaluations, and fostering a culture of continuous improvement
EDUCATION
Biju Patnaik University of Technology, Odisha
Bachelor of Technology - BTech, Computer Science
ABOUT ABINASH BEHERA
I am a NextGen, USA certified AI Product Manager (award-winner) with 13 years of experience across leading Product and Quality EngineeringI am seeking opportunities in owning end-to-end product lifecycle for custom Gen AI/Agentic AI & ML applications by leveraging deep understanding of gathering & translating business needs, implementing vision-based AI systems, applying human-centred design principles, and technological innovation & creativity to solve complex problemsSecured 1st position in “NextTrade” - Capstone Project, for its innovative use of AI, strategic execution, and meaningful business impact, an excellent demonstration of applied AI Product LeadershipSound knowledge of AI Product Management tools such as: Lovable, Bolt, Cursor, OpenAPI, Relevanceai, Agentic AI modelling, Colab,Firecrawl, N8N, Hugging Face models, Plexe, AWS, GitHub Copilot, Supabase, Postman, MavenHands-on experience with CPQ, B2B Commerce, and Billing practice; managed product pricing using Salesforce CPQ, E-Commerce Ordering Integration with the Order fulfilment tool (NetSuite), integration with the payment gateway, project management, and moreBuilt Automation tools, Products in Salesforce Accelerators, Subscription management platform in Salesforce, and Quote to Cash flowWorked with the industry-leading and emerging technologies to support critical applications and the most promising new use cases for ML and AI while championing system reliability, risk, performance, and operational efficiency throughout the product lifecycleAdept at fostering partnerships with clients and stakeholders that enable collaboration towards shared goals, and providing training and documentation materials that enable self-service adoption for customers and effective contribution models with partnersAdept at building the Foundation by architecting and delivering core platform capabilities such as- Model Context Protocol layers for injecting structured data into AI workflows- Agent frameworks with planning, memory, and tools integration (using ethical AI principles)- LLM evaluation frameworks, such as OpenAI Evals, to assess and improve the performance, reliability, and safety of AI applications- Evaluating pipelines for safety, fairness, and domain alignment; Model orchestration, fine-tuning, and inference APIs- Lead cross-functional delivery with Engineering, ML ops, and Design teams to bring products from concept to scale
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