Vikram A. — Senior Software Engineer

𝗦𝗲𝗻𝗶𝗼𝗿 𝗕𝗮𝗰𝗸𝗲𝗻𝗱 & 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 with experience designing and operating 𝗰𝗹𝗼𝘂𝗱-𝗻𝗮𝘁𝗶𝘃𝗲, 𝗰𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿𝗶𝘇𝗲𝗱 𝗺𝗶𝗰𝗿𝗼𝘀𝗲𝗿𝘃𝗶𝗰𝗲𝘀 at scale using Kubernetes (EKS), Docker, AWS, Java, Python, Kafka, and FluentD. Specialized in streaming systems, OTT pipelines, optimization problems, ad-tech, autoscaling, and 𝗵𝗶𝗴𝗵-𝗮𝘃𝗮𝗶𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲𝘀. Designed scalable backend systems used across 𝗥𝗼𝗸𝘂, 𝗔𝗻𝗱𝗿𝗼𝗶𝗱 𝗧𝗩, 𝗶𝗢𝗦, 𝗔𝗽𝗽𝗹𝗲 𝗧𝗩, 𝗙𝗶𝗿𝗲𝗧𝗩, 𝗖𝗵𝗿𝗼𝗺𝗲𝗰𝗮𝘀𝘁, 𝗦𝗺𝗮𝗿𝘁 𝗧𝗩𝘀, 𝗮𝗻𝗱 𝗺𝘂𝗹𝘁𝗶-𝗿𝗲𝗴𝗶𝗼𝗻 𝗰𝗹𝗼𝘂𝗱 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁𝘀. Strong foundation in 𝘥𝘢𝘵𝘢 𝘴𝘵𝘳𝘶𝘤𝘵𝘶𝘳𝘦𝘴, 𝘢𝘭𝘨𝘰𝘳𝘪𝘵𝘩𝘮𝘴, 𝘴𝘺𝘴𝘵𝘦𝘮 𝘥𝘦𝘴𝘪𝘨𝘯, 𝘥𝘪𝘴𝘵𝘳𝘪𝘣𝘶𝘵𝘦𝘥 𝘤𝘰𝘮𝘱𝘶𝘵𝘪𝘯𝘨, 𝘰𝘣𝘴𝘦𝘳𝘷𝘢𝘣𝘪𝘭𝘪𝘵𝘺, 𝘢𝘯𝘥 𝘱𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦 𝘰𝘱𝘵𝘪𝘮𝘪𝘻𝘢𝘵𝘪𝘰𝘯. 𝗞𝗲𝘆 𝗮𝗰𝗵𝗶𝗲𝘃𝗲𝗺𝗲𝗻𝘁𝘀 𝗶𝗻𝗰𝗹𝘂𝗱𝗲: • Implemented 𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝗵𝗮𝘀𝗵𝗶𝗻𝗴 for deterministic session routing, improving availability under pod churn and reducing DB load. • Delivered 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗮𝘂𝘁𝗼𝘀𝗰𝗮𝗹𝗶𝗻𝗴 𝘂𝘀𝗶𝗻𝗴 𝗞𝗘𝗗𝗔, right-sizing container resources → ~45% reduction in cloud compute costs. • Built microservices and backend tooling for 𝘃𝗶𝗱𝗲𝗼 𝗰𝗿𝗲𝗮𝘁𝗶𝘃𝗲 𝗱𝗲𝗱𝘂𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 (Python, Kafka, FluentD, librosa, videohash). • Created a 𝗱𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗹𝗼𝗮𝗱-𝘁𝗲𝘀𝘁𝗶𝗻𝗴 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 (Node.js orchestrator + parallel workers) for validating Kubernetes microservices at scale. • Led 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀 𝗶𝗻 𝗺𝗮𝗻𝗶𝗳𝗲𝘀𝘁 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 (DASH), streaming resilience, caching strategies, and device playback logic. • Experience with 𝗖𝗜/𝗖𝗗 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀, 𝗼𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝘀𝘆𝘀𝘁𝗲𝗺𝘀, 𝗮𝗹𝗲𝗿𝘁 𝘁𝘂𝗻𝗶𝗻𝗴, 𝗹𝗼𝗴𝗴𝗶𝗻𝗴 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀, 𝗮𝗻𝗱 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗽𝗿𝗼𝗳𝗶𝗹𝗶𝗻𝗴. Comfortable working across cloud platforms, distributed systems, and large-scale service design. Strong collaborator with experience supporting SRE, platform, and product engineering teams. Suited for roles involving: 𝘣𝘢𝘤𝘬𝘦𝘯𝘥 𝘦𝘯𝘨𝘪𝘯𝘦𝘦𝘳𝘪𝘯𝘨, 𝘤𝘭𝘰𝘶𝘥 𝘱𝘭𝘢𝘵𝘧𝘰𝘳𝘮𝘴, 𝘒𝘶𝘣𝘦𝘳𝘯𝘦𝘵𝘦𝘴 𝘦𝘤𝘰𝘴𝘺𝘴𝘵𝘦𝘮𝘴, 𝘮𝘪𝘤𝘳𝘰𝘴𝘦𝘳𝘷𝘪𝘤𝘦𝘴 𝘢𝘳𝘤𝘩𝘪𝘵𝘦𝘤𝘵𝘶𝘳𝘦, 𝘥𝘪𝘴𝘵𝘳𝘪𝘣𝘶𝘵𝘦𝘥 𝘴𝘺𝘴𝘵𝘦𝘮𝘴, 𝘖𝘛𝘛/𝘴𝘵𝘳𝘦𝘢𝘮𝘪𝘯𝘨 𝘴𝘺𝘴𝘵𝘦𝘮𝘴, 𝘱𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦 𝘦𝘯𝘨𝘪𝘯𝘦𝘦𝘳𝘪𝘯𝘨, 𝘢𝘥-𝘵𝘦𝘤𝘩, 𝘪𝘯𝘧𝘳𝘢𝘴𝘵𝘳𝘶𝘤𝘵𝘶𝘳𝘦 𝘳𝘦𝘴𝘪𝘭𝘪𝘦𝘯𝘤𝘦, 𝘢𝘯𝘥 𝘭𝘢𝘳𝘨𝘦-𝘴𝘤𝘢𝘭𝘦 𝘴𝘺𝘴𝘵𝘦𝘮 𝘳𝘦𝘭𝘪𝘢𝘣𝘪𝘭𝘪𝘵𝘺.

Stackforce AI infers this person is a Backend Engineer specializing in cloud-native and streaming systems for the media industry.

Location: Pune, Maharashtra, India

Experience: 7 yrs 10 mos

Skills

Backend Engineering
Cloud Computing
Streaming Systems
Software Development

Career Highlights

Expert in building scalable backend systems.
Proven track record in cloud-native architecture.
Strong collaborator with cross-functional teams.

Work Experience

Warner Bros. Discovery

Senior Software Engineer (3 yrs 1 mo)

Discovery

Software Engineer (1 yr 9 mos)

Siemens PLM Software

Software Engineer (1 yr 6 mos)

Software Engineer Associate (1 yr 6 mos)

GS Lab

Internship Project (5 mos)

Education

Bachelor of Engineering - BE at Pune Institute of Computer Technology

High School Diploma at Amrutvahini Model School

Vikram A.

Senior Software Engineer

Pune, Maharashtra, India7 yrs 10 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in building scalable backend systems.
Proven track record in cloud-native architecture.
Strong collaborator with cross-functional teams.

Stackforce AI infers this person is a Backend Engineer specializing in cloud-native and streaming systems for the media industry.

Contact

Skills

Core Skills

Backend EngineeringCloud ComputingStreaming SystemsSoftware Development

Other Skills

Kubernetescloud-native systemsautoscalingstreaming reliabilityobservabilityKEDAEKSPythonKafkaFluentDNode.jsstreaming pipelinescodec filteringad deliverymemory management

About

Experience

7 yrs 10 mos

Total Experience

2 yrs 7 mos

Average Tenure

3 yrs 1 mo

Current Experience

Warner bros. discovery

Senior Software Engineer

Apr 2023 – Present · 3 yrs 1 mo · Pune, Maharashtra, India · On-site

I design and operate backend and cloud-native systems that stay predictable under scale, traffic spikes, and pod churn. My work spans distributed systems, 𝘒𝘶𝘣𝘦𝘳𝘯𝘦𝘵𝘦𝘴 𝘰𝘱𝘵𝘪𝘮𝘪𝘻𝘢𝘵𝘪𝘰𝘯, 𝘢𝘶𝘵𝘰𝘴𝘤𝘢𝘭𝘪𝘯𝘨, 𝘴𝘵𝘳𝘦𝘢𝘮𝘪𝘯𝘨 𝘳𝘦𝘭𝘪𝘢𝘣𝘪𝘭𝘪𝘵𝘺, 𝘢𝘯𝘥 𝘢𝘥-𝘥𝘦𝘭𝘪𝘷𝘦𝘳𝘺 𝘪𝘯𝘧𝘳𝘢𝘴𝘵𝘳𝘶𝘤𝘵𝘶𝘳𝘦 𝘢𝘤𝘳𝘰𝘴𝘴 𝘨𝘭𝘰𝘣𝘢𝘭 𝘢𝘶𝘥𝘪𝘦𝘯𝘤𝘦𝘴.
𝗞𝗲𝘆 𝗖𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻𝘀
Implemented 𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝗵𝗮𝘀𝗵𝗶𝗻𝗴 to replace fragile session stickiness, providing deterministic routing and stabilizing services during Kubernetes autoscaling, pod churn, and rolling updates.
𝗥𝗲𝗱𝘂𝗰𝗲𝗱 𝗰𝗼𝗺𝗽𝘂𝘁𝗲 𝘀𝗽𝗲𝗻𝗱 𝗯𝘆 ~𝟰𝟱% through KEDA-based predictive autoscaling, right-sizing workloads, and optimizing EKS resource allocation during off-peak and surge events.
𝗜𝗻𝗰𝗿𝗲𝗮𝘀𝗲𝗱 𝗰𝗹𝘂𝘀𝘁𝗲𝗿 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 by applying right-sizing heuristics, improving pod placement density and reducing required node count.
Built a 𝗰𝗿𝗲𝗮𝘁𝗶𝘃𝗲-𝗱𝗲𝗱𝘂𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗺𝗶𝗰𝗿𝗼𝘀𝗲𝗿𝘃𝗶𝗰𝗲 (Python, Kafka, FluentD, librosa/videohash) that removed redundant transcoding and lowered CDN/storage overhead.
Developed a 𝗱𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗹𝗼𝗮𝗱-𝘁𝗲𝘀𝘁𝗶𝗻𝗴 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 (Node.js orchestration, parallel workers, Slack reporting) to validate microservice behavior, latency budgets, and scaling thresholds before production rollout.
Strengthened streaming reliability by designing 𝗳𝗮𝗹𝗹𝗯𝗮𝗰𝗸 𝗮𝗻𝗱 𝗳𝗮𝗶𝗹-𝗳𝗮𝘀𝘁 𝗺𝗲𝗰𝗵𝗮𝗻𝗶𝘀𝗺𝘀 that reduced 5xx failures during pod restarts and traffic surges.
Owned 𝗼𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆 improvements, including alert tuning, actionable logging signals, and edge-case instrumentation, lowering MTTR and improving on-call confidence.
𝗦𝗵𝗶𝗽 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗽𝗹𝗮𝘆𝗯𝗼𝗼𝗸𝘀: Authored autoscaling templates, migration guides, and internal docs used across teams for cloud deployments and scaling patterns.

Kubernetescloud-native systemsautoscalingstreaming reliabilityobservabilityBackend Engineering+1

Discovery

Software Engineer

Jul 2021 – Apr 2023 · 1 yr 9 mos · Pune, Maharashtra, India

I engineered playback-critical components for live and VOD streaming pipelines across 𝗥𝗼𝗸𝘂, 𝗔𝗻𝗱𝗿𝗼𝗶𝗱/𝗧𝗩, 𝗶𝗢𝗦, 𝗙𝗶𝗿𝗲𝗧𝗩, 𝗔𝗽𝗽𝗹𝗲 𝗧𝗩, 𝗖𝗵𝗿𝗼𝗺𝗲𝗰𝗮𝘀𝘁, 𝗮𝗻𝗱 𝗦𝗺𝗮𝗿𝘁 𝗧𝗩𝘀.
𝗞𝗲𝘆 𝗖𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻𝘀:
𝗥𝗲𝗱𝘂𝗰𝗲𝗱 𝗠𝗣𝗘𝗚-𝗗𝗔𝗦𝗛 𝗺𝗮𝗻𝗶𝗳𝗲𝘀𝘁 𝘀𝗶𝘇𝗲 𝗯𝘆 ~𝟴𝟱% via codec and representation filtering, improving startup latency and memory usage on constrained devices.
Built 𝗱𝘆𝗻𝗮𝗺𝗶𝗰 𝗨𝗥𝗟 𝘀𝘂𝗯𝘀𝘁𝗶𝘁𝘂𝘁𝗶𝗼𝗻 𝗳𝗼𝗿 𝗥𝗼𝗸𝘂 (BrightScript + templated manifests) enabling personalized SSAI ad delivery and consistent cross-device behavior.
Designed a 𝘀𝗹𝗶𝗱𝗶𝗻𝗴-𝘄𝗶𝗻𝗱𝗼𝘄 𝗮𝗱-𝗯𝗿𝗲𝗮𝗸 𝗺𝗮𝗻𝗮𝗴𝗲𝗿 for Chromecast to handle tight memory constraints, preventing playback failures and improving ad completion rates.
Implemented 𝗹𝗮𝘁𝗲-𝘁𝗲𝗿𝗺𝗶𝗻𝗮𝘁𝗶𝗼𝗻 𝗿𝗲𝗰𝗼𝘃𝗲𝗿𝘆 𝗳𝗼𝗿 𝗹𝗶𝘃𝗲 𝗮𝗱 𝗯𝗿𝗲𝗮𝗸𝘀 using static-segment (filler) stitching to avoid session drops and revenue loss.
Resolved 𝗰𝗿𝗼𝘀𝘀-𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗣𝟬 𝗶𝗻𝗰𝗶𝗱𝗲𝗻𝘁𝘀 by debugging edge cases, improving instrumentation, and collaborating closely with 𝘱𝘭𝘢𝘺𝘣𝘢𝘤𝘬, 𝘊𝘋𝘕, 𝘘𝘈, 𝘢𝘯𝘥 𝘚𝘙𝘌 𝘵𝘦𝘢𝘮𝘴.
Delivered improvements to caching, rendition selection, and failover behavior to 𝘀𝘁𝗿𝗲𝗻𝗴𝘁𝗵𝗲𝗻 𝗤𝗼𝗘 𝗮𝗰𝗿𝗼𝘀𝘀 𝗱𝗲𝘃𝗶𝗰𝗲 𝗲𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺𝘀.

streaming pipelinescodec filteringad deliverymemory managementStreaming SystemsBackend Engineering

Siemens plm software

2 roles

Software Engineer

Promoted

Dec 2019 – Jun 2021 · 1 yr 6 mos

I improved 𝘤𝘭𝘰𝘶𝘥-𝘣𝘢𝘴𝘦𝘥 𝘊𝘈𝘋 𝘴𝘦𝘳𝘷𝘪𝘤𝘦𝘴, 𝘢𝘶𝘵𝘰𝘮𝘢𝘵𝘦𝘥 𝘪𝘯𝘧𝘳𝘢𝘴𝘵𝘳𝘶𝘤𝘵𝘶𝘳𝘦 𝘸𝘰𝘳𝘬𝘧𝘭𝘰𝘸𝘴, 𝘢𝘯𝘥 𝘰𝘱𝘵𝘪𝘮𝘪𝘻𝘦𝘥 𝘊𝘐/𝘊𝘋 𝘱𝘪𝘱𝘦𝘭𝘪𝘯𝘦𝘴 for engineering productivity.
𝗞𝗲𝘆 𝗖𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻𝘀:
Adopted 𝗦𝗲𝗿𝘃𝗲𝗿𝗹𝗲𝘀𝘀 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 for cloud based service in AWS
𝗖𝘂𝘁 𝗗𝗼𝗰𝗸𝗲𝗿 𝗯𝘂𝗶𝗹𝗱 𝘁𝗶𝗺𝗲 𝗳𝗿𝗼𝗺 𝟮𝟬+ 𝗺𝗶𝗻𝘂𝘁𝗲𝘀 𝘁𝗼 ~𝟰 𝗺𝗶𝗻𝘂𝘁𝗲𝘀 and 𝗿𝗲𝗱𝘂𝗰𝗲𝗱 𝗶𝗺𝗮𝗴𝗲 𝘀𝗶𝘇𝗲 𝗯𝘆 ~𝟰𝟱%, accelerating release cycles and CI pipeline throughput.
𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗔𝗪𝗦 𝗽𝗿𝗼𝘃𝗶𝘀𝗶𝗼𝗻𝗶𝗻𝗴 using boto3/GitLab CI, 𝗿𝗲𝗱𝘂𝗰𝗶𝗻𝗴 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝘁𝗶𝗺𝗲 𝗯𝘆 ~𝟵𝟬% and improving environment consistency.
𝗙𝗶𝘅𝗲𝗱 𝟲𝟬+ 𝗰𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝘃𝘂𝗹𝗻𝗲𝗿𝗮𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀 via ECR scanning and remediation workflows.
Built REST APIs in .NET Core and 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲𝗱 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝗖𝗔𝗗 𝗰𝗼𝗻𝘃𝗲𝗿𝘁𝗲𝗿𝘀 𝗶𝗻𝘁𝗼 𝗰𝗹𝗼𝘂𝗱-𝗻𝗮𝘁𝗶𝘃𝗲 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀.
𝗔𝘂𝘁𝗵𝗼𝗿𝗲𝗱 𝗱𝗲𝘁𝗮𝗶𝗹𝗲𝗱 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗮𝗹 𝗮𝗻𝗱 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 to streamline onboarding and reduce ambiguity across teams.
Built 𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝗼𝗿𝘀 & 𝗽𝗹𝘂𝗴𝗴𝗮𝗯𝗹𝗲 𝗥𝗲𝗮𝗰𝘁 𝘄𝗶𝗱𝗴𝗲𝘁𝘀 for cloud service in Mendix
Adopted 𝗚𝗶𝘁𝗟𝗮𝗯 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝘆, 𝗘𝗖𝗥, 𝗦𝗼𝗻𝗮𝗿𝗤𝘂𝗯𝗲

cloud-based CAD servicesAWSDockerREST APIsCloud ComputingSoftware Development

Software Engineer Associate

Jun 2018 – Dec 2019 · 1 yr 6 mos

Developed and maintained 3D desktop-based CAD translator in C++
Wrote elegant, maintainable, stable code in C++
Helped move existing proprietary 3D CAD translators from desktop to cloud
Created test ui client in Angular for consuming REST APIs

C++AngularREST APIsSoftware Development

Gs lab

Internship Project

Sep 2017 – Feb 2018 · 5 mos · Pune, Maharashtra, India

Led and managed team of 4 to develop a web-portal for farmers that would help them grow crops most suitable to their geographical location and weather conditions
Estimated crop yield given the location, soil conditions, weather information
Technologies: MySQL, Java, Spring MVC, Python

MySQLJavaSpring MVCPythonSoftware Development