Abhishek Jaiswal

CEO

New Delhi, Delhi, India4 yrs 11 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Specialized in data streaming and event-driven architectures.
Delivered multiple ML prototypes on streaming data.
7x certified in MuleSoft and Salesforce.

Stackforce AI infers this person is a Solutions Engineer with expertise in SaaS and data streaming technologies.

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Skills

Core Skills

Apache KafkaSolutions Engineering

Other Skills

Confluent Cloudevent-driven architecturesreal-time analyticsfraud detectionintegration modernizationtechnical discoveryPoCsdata streamingKafkaevent-driven designWeb TechnologiesRobotic Process Automation (RPA)Problem SolvingGen aiData Engineering

About

I’m a Solutions Engineer specializing in data streaming, event-driven architectures, and enterprise integrations using Apache Kafka, Confluent Cloud, MuleSoft, and Salesforce. Over ~5 years, I’ve helped customers design and implement low-latency, scalable architectures for use cases like real-time analytics, fraud detection, and integration modernization across financial services, healthcare, and SaaS. In my current role at Confluent, I work with customers end-to-end: understanding business goals, designing architectures, building PoCs, and driving technical wins in the sales cycle. Previously at Apisero/NTT DATA, I delivered integrations and APIs on MuleSoft and Salesforce for enterprise clients. I’m passionate about AI/ML on streaming data, have built multiple ML prototypes (time series forecasting, classification, NLP), and regularly contribute to Kafka/Flink community learning and content.

Experience

4 yrs 11 mos

Total Experience

1 yr 3 mos

Average Tenure

1 yr

Current Experience

Confluent

Solutions Engineer

May 2025 – Present · 1 yr · Remote

. Design event-driven architectures on Apache Kafka and Confluent Cloud for enterprise customers, enabling real-time use cases such as fraud detection, clickstream analytics, and integration modernisation.
.Lead technical discovery, demos, and PoCs across the sales cycle, translating business requirements into scalable streaming and integration solutions that drive technical win decisions.
. Build and maintain reusable reference architectures, demo assets, and best-practice patterns for data streaming, reducing PoC delivery time and improving consistency across customer engagements.
. Collaborate with customer engineering, field teams, and product management to capture feedback from real-world deployments and influence roadmap priorities around data streaming, governance, and integrations.
. Deliver technical workshops and enablement sessions on Kafka, Confluent Cloud, and event-driven design for customer and partner teams, improving adoption and overall solution quality.

Apache KafkaConfluent Cloudevent-driven architecturesreal-time analyticsfraud detectionintegration modernization+4