Bright Vision Technologies

Security Engineer

• Designing, implementing, and operating security controls across Oracle Cloud Infrastructure (OCI), Oracle Cloud Applications, and hybrid Oracle environments.
• Defining security architecture, hardening cloud workloads, managing identity and access, leading vulnerability and compliance programs, and responding to security incidents.
• Working closely with cross-functional partners — product, design, engineering, operations, and business stakeholders.
• Translating ambiguous requirements into well-engineered solutions and expected to raise the bar through code review, design review, and mentorship of more junior engineers.

Oracle Cloud Security Engineer

Cloud Engineer

• Architect, deploy, and operate enterprise-grade OCI landing zones, compartments, and tenancy structures aligned with internal governance and compliance standards
• Design and implement OCI networking topologies, including VCNs, subnets, gateways, FastConnect, IPSec VPN, and DRG-based hub-and-spoke architectures
• Build and maintain OCI infrastructure-as-code using Terraform and OCI Resource Manager, with version control, peer review, and automated validation
• Implement IAM policies, federation with corporate identity providers, and strong RBAC patterns using OCI Identity Domains
• Design and operate OCI compute (VMs, bare-metal, OKE for Kubernetes) and storage services (Object, Block, File, Archive) optimized for workload patterns
• Operate OCI database services, including Autonomous Database, Exadata Cloud, MySQL HeatWave, and Base Database, in close partnership with DBA teams
• Build CI/CD pipelines on OCI DevOps service or external platforms (Jenkins, GitHub Actions) for both infrastructure and applications
• Implement observability using OCI Monitoring, Logging, APM, and integrations with third-party observability stacks
• Drive ongoing cost optimization through right-sizing, lifecycle management, and architectural simplification
• Design disaster-recovery and business-continuity solutions across OCI regions and availability domains
• Strengthen security posture using OCI Cloud Guard, Security Zones, Vault, and Data Safe, and lead remediation of findings
• Advise application development teams on OCI-native design patterns and best practices
• Develop automation tooling in Python, Bash, and Terraform to reduce operational toil
• Mentor junior engineers and contribute to internal cloud communities of practice.

Oracle Cloud Infrastructure Engineer

Engineer

• Design, deploy, and operate enterprise-grade Red Hat OpenShift container platforms running mission-critical workloads across on-premises and cloud environments
• Own the end-to-end platform lifecycle — from cluster provisioning and hardening, through workload onboarding and developer enablement, to ongoing operations and continuous improvement
• Architect, provision, and operate Red Hat OpenShift clusters across on-premises, virtualized, and major cloud environments
• Design and implement multi-tenant OpenShift platforms
• Automate cluster lifecycle operations — installation, upgrades, scaling, and decommissioning
• Onboard application development teams to the platform
• Operate OpenShift networking and manage OpenShift storage strategies
• Implement comprehensive monitoring, logging, and tracing
• Harden the platform in collaboration with security teams
• Design and maintain robust CI/CD pipelines on OpenShift
• Develop disaster-recovery and backup strategies
• Plan, test, and execute cluster upgrades
• Partner with application teams to right-size workloads
• Continuously evolve platform tooling and developer experience
• Mentor junior engineers.

OpenShift Engineer

Solutions Engineer

• Design and develop integration flows in MuleSoft Anypoint Studio, including DataWeave transformations, error handling, and reusable connectors.
• Apply API-led connectivity (System, Process, Experience APIs) to deliver reusable, composable integration assets.
• Design and publish well-documented APIs using API Designer and the Anypoint Exchange.
• Configure and manage runtimes (CloudHub, Runtime Fabric, Hybrid) appropriate to workload requirements.
• Implement strong API security using OAuth2, mTLS, JWT, and Anypoint API Manager policies.
• Build event-driven integrations using Anypoint MQ, Salesforce Platform Events, or Kafka.
• Optimize integration performance, including pooling, caching, parallel processing, and message size management.
• Build CI/CD pipelines for MuleSoft applications using Maven, Anypoint CLI, GitHub Actions, or Jenkins.
• Migrate legacy integrations from other middleware (Oracle SOA, BizTalk) to MuleSoft.
• Implement comprehensive monitoring and alerting using Anypoint Monitoring and external observability tools.
• Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures — so that the system remains supportable, auditable, and easy to onboard new engineers onto over time.
• Mentor junior developers and contribute to internal integration patterns and standards.
• Collaborate closely with security, enterprise architecture, and application development teams, gathering requirements, aligning on technical approach, and ensuring that delivered solutions meet both functional needs and broader engineering and operational standards.

MuleSoft Integration Engineer

Architect

• Lead the design and evolution of large-scale microservices ecosystems built on modern container platforms and cloud-native technology stacks
• Define microservices architecture standards, service boundaries, and decomposition strategies aligned with domain-driven design principles
• Lead the modernization of legacy monoliths into well-bounded, independently deployable services with clear ownership
• Design service communication patterns leveraging REST, gRPC, asynchronous messaging, and event streaming as appropriate
• Establish API contracts, schema governance, and versioning strategies that enable safe evolution of services over time
• Architect resilient distributed systems incorporating circuit breakers, retries, bulkheads, and graceful degradation patterns
• Define data ownership models, transactional boundaries, and patterns such as outbox, saga, and CQRS where appropriate
• Lead the design of platform capabilities including service mesh, API gateway, identity propagation, and shared observability
• Drive performance engineering, capacity planning, and scalability analysis across critical service domains
• Establish CI/CD, testing, and deployment standards optimized for high-frequency, low-risk service releases
• Define observability standards including structured logging, distributed tracing, and SLO-driven monitoring
• Collaborate with security teams to ensure zero-trust principles, secrets management, and runtime protection are embedded
• Mentor engineers and tech leads on microservices best practices and anti-pattern avoidance
• Lead architecture reviews and provide guidance on service design proposals across multiple teams
• Continuously evaluate emerging cloud-native technologies for adoption based on maturity and strategic fit.

Microservices Architect

• Design and execute fine-tuning experiments for large language models using supervised, DPO, RLHF, and related techniques
• Lead dataset construction, curation, and quality assurance processes for instruction tuning and preference data
• Build scalable training pipelines on top of modern distributed training frameworks
• Tune hyperparameters, optimizer configurations, and training stability strategies for large-model fine-tuning
• Implement parameter-efficient fine-tuning techniques such as LoRA, QLoRA, and adapter-based methods
• Design rigorous evaluation suites including automated benchmarks, human evaluation, and capability-specific probes
• Implement safety, refusal, and policy evaluations to track model behavior across releases
• Operate large-scale training jobs on GPU clusters, diagnosing failures and recovering training state reliably
• Optimize training throughput using mixed precision, sequence packing, and efficient attention implementations
• Manage model artifacts, lineage tracking, and reproducibility across many concurrent experiments
• Collaborate with product, research, and platform teams to align fine-tuning roadmaps with business needs
• Document training methodology, results, and decisions clearly for technical and non-technical audiences
• Mentor engineers on fine-tuning best practices, evaluation rigor, and responsible deployment
• Stay current with LLM research and translate advances into production-ready fine-tuning recipes.

LLM Fine-Tuning Engineer

Platform Engineer

• Architect, deploy, and operate large-scale Apache Kafka or Confluent Platform clusters
• Design partitioning, replication, and topic strategies
• Implement strong security on Kafka clusters
• Operate Schema Registry, Kafka Connect, KSQL/ksqlDB, and Kafka Streams in production
• Build and operate Kafka Connect pipelines integrating sources and sinks
• Design HA/DR strategies for Kafka
• Build CI/CD pipelines for Kafka topic, ACL, and connector configurations
• Implement comprehensive observability using Prometheus, Grafana, Datadog, or Confluent Control Center
• Drive Kafka cost and capacity optimization
• Onboard application teams to Kafka
• Lead incident response and post-incident reviews
• Mentor and coach junior and mid-level engineers
• Maintain comprehensive, current technical documentation
• Continuously evaluate emerging streaming technologies

Kafka Platform Engineer

Backend Engineer

• Architect, design, develop, and maintain enterprise-grade web applications and distributed systems
• Responsible for the end-to-end engineering lifecycle
• Write production-quality code
• Deploy cloud-native services and support them through their operational lifespan
• Design, build, and continuously refine scalable microservices using Java and the Spring Boot framework
• Author secure, well-tested, and high-quality production code
• Develop responsive, component-based front-end applications using React
• Design and implement RESTful APIs and event-driven integrations
• Actively participate in architecture and design discussions
• Continuously profile and optimize application performance
• Implement and maintain robust state management patterns for complex front-end applications
• Develop comprehensive automated test suites
• Contribute meaningfully to CI/CD pipeline design and deployment automation
• Proactively identify system bottlenecks and drive remediation efforts
• Collaborate effectively within Agile/Scrum delivery teams
• Maintain clear, current, and comprehensive technical documentation

Java Full Stack Developer

• Design and build connected, data-driven industrial systems spanning the factory floor to enterprise cloud platforms
• Architect end-to-end IIoT solutions, including edge data acquisition, secure connectivity, cloud ingestion, real-time analytics, and operational dashboards
• Work closely with cross-functional partners to translate ambiguous requirements into well-engineered solutions
• Mentor junior and mid-level engineers through code review, design review, pair programming, and structured knowledge sharing

Industrial IoT Engineer

Software Engineer

• Design, develop, and operate end-to-end big-data pipelines on Hadoop, ingesting data from various sources.
• Build robust ETL/ELT workflows using Apache Spark, Hive, Pig, and Sqoop.
• Develop high-throughput streaming data pipelines using Kafka, Spark Streaming, or Flink.
• Optimize Spark and MapReduce jobs to meet SLAs at minimal cost.
• Design and maintain data models and storage layouts on HDFS and related formats.
• Implement data governance and quality controls.
• Build robust monitoring and logging strategies for big-data pipelines.
• Partner with data scientists to deliver reliable datasets.
• Automate pipeline orchestration using Airflow or Oozie.
• Continuously evaluate and adopt new technologies in the big-data ecosystem.
• Mentor junior engineers and contribute to the team’s engineering standards.

Hadoop Developer

Systems Engineer

• Design and implement high-performance CUDA kernels for compute-intensive workloads across AI and HPC use cases.
• Profile and optimize GPU code using tools such as Nsight Systems, Nsight Compute, and CUDA profilers.
• Tune memory access patterns, occupancy, register usage, and shared memory utilization for peak performance.
• Develop highly optimized libraries for linear algebra, attention, and other ML primitives.
• Optimize multi-GPU and multi-node training using NCCL, RDMA, and high-performance networking.
• Implement custom operators and fused kernels in PyTorch, JAX, or Triton.
• Collaborate with ML engineers to identify performance bottlenecks in training and inference pipelines.
• Develop benchmarks and regression tests to safeguard performance over time.
• Evaluate new GPU architectures and feature sets, and advise on adoption strategy.
• Contribute to compiler-level optimizations for tensor programs where appropriate, working at the boundary between ML frameworks and underlying accelerator codegen to unlock performance not reachable through framework-level tuning alone.
• Optimize memory hierarchy usage across HBM, L2, shared memory, and registers.
• Implement mixed-precision and quantized compute paths that maximize accelerator throughput while preserving numerical fidelity within bounds acceptable for the target workloads.
• Document performance characteristics, design decisions, and tuning playbooks for internal teams.
• Stay current with GPU architecture, CUDA evolution, and emerging accelerator technologies.

GPU Systems Engineer, CUDA

• Design and implement performant backend services and APIs in Go, with strong attention to concurrency, error handling, and resource management.
• Build cloud-native applications using Go and Kubernetes-native libraries, applying idiomatic Go patterns, well-defined module boundaries, and operational hooks that make the resulting services easy to deploy and run.
• Develop CLI tools, Kubernetes controllers, and custom operators for internal platforms, designing clear command surfaces, robust error handling, and reconciliation logic that operates safely in long-running environments.
• Implement gRPC and REST APIs with appropriate observability and security.
• Profile and optimize Go applications for memory, GC, and goroutine behavior, applying systematic measurement, targeted improvements, and data-driven validation to deliver quantifiable gains in throughput, latency, or resource efficiency.
• Integrate with messaging systems (Kafka, NATS) and data stores (PostgreSQL, Redis, etcd).
• Build comprehensive automated tests, including unit, integration, and benchmark tests.
• Implement structured logging, metrics emission, and distributed tracing throughout services so that operators and on-call engineers have the signals they need to diagnose issues and reason about system behavior.
• Lead code reviews and uphold engineering standards in Go projects.
• Mentor and coach junior and mid-level engineers through code review, design review, pair programming, and structured knowledge sharing, helping the broader team grow in technical maturity and confidence over time.
• Contribute meaningfully to internal Go libraries, shared platform tooling, and reusable patterns that accelerate development across multiple engineering teams and codify hard-won best practices.
• Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures — so that the system remains supportable, auditable, and easy to onboard new engineers onto over time.
• Continuously evaluate Go ecosystem evolution and contribute to internal patterns.

Golang Developer

• Design and develop Boomi integration processes, including connectors, data maps, decisions, branches, and exception handling.
• Apply Boomi’s low-code patterns alongside custom scripting (Groovy, JavaScript) for complex transformations.
• Build connectors and use the Boomi Connector SDK where required.
• Configure and manage Atom and Molecule runtimes appropriate to workload needs.
• Design and operate API management strategies using Boomi API Management.
• Implement secure authentication patterns including OAuth2, mTLS, and certificate-based authentication.
• Build event-driven and pub/sub patterns using Boomi Flow, Event Streams, and external messaging platforms.
• Develop CI/CD pipelines for Boomi processes using Boomi’s deployment APIs, GitHub Actions, or Jenkins.
• Lead migration efforts to retire legacy integrations from other middleware platforms to Boomi, planning phased cutovers, building backward-compatibility shims where needed, and ensuring each migration step is reversible and well-monitored.
• Implement comprehensive monitoring, alerting, and operational dashboards, applying disciplined engineering practices and partnering closely with stakeholders to ensure outcomes are durable, well-documented, and aligned with broader team and platform standards.
• Profile and optimize performance of high-volume Boomi integrations, applying systematic measurement, targeted improvements, and data-driven validation to deliver quantifiable gains in throughput, latency, or resource efficiency.
• Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures — so that the system remains supportable, auditable, and easy to onboard new engineers onto over time.
• Mentor junior developers and contribute to internal integration patterns and standards.

Integration Engineer

• Design and implement enterprise-grade Azure cloud architectures spanning compute, networking, storage, identity, and data services, with explicit attention to scalability, security, and total cost of ownership.
• Develop, maintain, and continuously improve infrastructure-as-code using Terraform, Bicep, or ARM templates, treating infrastructure changes with the same rigor as application code through version control and peer review.
• Configure and manage Azure landing zones, virtual networks, subnets, route tables, and network security groups to enforce strong segmentation and least-privilege connectivity between workloads.
• Implement secure identity, access management, and governance controls using Azure Active Directory, conditional access, role-based access control, and Azure Policy to ensure compliance with internal and regulatory standards.
• Architect and operate Azure Kubernetes Service (AKS) clusters, including node pool design, auto-scaling, network policy, and integration with container registries and service meshes.
• Deploy, scale, and tune Azure data and analytics platforms such as Azure SQL, Cosmos DB, Synapse Analytics, Data Factory, and Event Hubs to meet specific workload patterns and SLAs.
• Build and operate comprehensive CI/CD pipelines using Azure DevOps or GitHub Actions, enabling fast, automated, and auditable releases of both infrastructure and application code.
• Design and implement robust observability practices using Azure Monitor, Log Analytics, Application Insights, and third-party tooling, with thoughtful dashboards, alerting, and SLO tracking.
• Drive Azure cost optimization initiatives, including right-sizing, reserved-instance planning, lifecycle policies, and architectural changes that meaningfully reduce monthly cloud spend.
• Implement disaster-recovery and business-continuity strategies, including backup, geo-replication, failover testing, and documented runbooks that have been validated through regular drills.
• Strengthen security posture by integrating Microsoft Defender for Cloud, Sentinel, key vault, and managed identities, and by routinely remediating findings from compliance scans.
• Collaborate closely with application teams to architect cloud-native solutions, advising on patterns, anti-patterns, and Azure-native services that best fit each problem domain.
• Develop automation scripts and tooling in PowerShell, Bash, and Python to streamline repetitive operational work and reduce time-to-resolution for common incidents.
• Mentor junior engineers, lead architecture reviews, and contribute actively to internal communities of practice around Azure and DevOps.

Azure Cloud Engineer

• Design, build, and operate large-scale, secure, and highly available cloud platforms on Amazon Web Services
• Architect, deploy, and operate enterprise-grade AWS environments across compute, networking, storage, identity, and managed data services
• Author and maintain production-quality infrastructure-as-code using Terraform, AWS CloudFormation, or AWS CDK
• Design multi-account AWS organizations and build secure VPC topologies
• Implement strong IAM strategies and design, deploy, and operate Amazon EKS clusters
• Operate AWS managed data and analytics services such as RDS, Aurora, and DynamoDB
• Build and maintain robust CI/CD pipelines using AWS tools
• Implement comprehensive observability and drive ongoing cost optimization
• Implement disaster-recovery and business-continuity capabilities
• Strengthen security posture using AWS security tools
• Advise application development teams on AWS-native design patterns
• Develop automation scripts and mentor junior engineers.