Top Software Engineer Jobs in Baltimore, MD

Senior engineer responsible for designing, building, and operating scalable data ingestion, processing, storage, and member-facing membership application. Drive architecture decisions, mentor engineers, build data pipelines, APIs, and ensure reliability, observability, CI/CD, and documentation while partnering with product and analytics stakeholders.

Lead design and implementation of the Libraries Platform: services, pipelines, and package index to build, verify, and serve secure reproducible libraries. Automate artifact creation, CVE remediation, SBOM/provenance generation, AI-assisted patching, and operate registry/mirroring, CI/CD integrations, reliability, observability, and incident response while mentoring engineers.

Design, implement, and maintain backend services and core APIs (primarily Scala). Collaborate on architecture, improve system reliability, and deliver production software for legal AI products.

Lead design and implementation of DSP algorithms in FPGA hardware, develop RTL with timing closure and resource optimization, integrate FPGA with Linux-based software using C/C++, test RF communication subsystems, and document system-level designs and integrations.

The Software Tools Engineer 1 automates requirement management and supports software productivity tools for federal projects, ensuring traceability and integration with project processes.

Lead full‑stack development of web applications using C#, ASP.NET (Web Forms or MVC), HTML, CSS, and JavaScript libraries. Code, test, integrate, and document solutions; mentor teams; design complex systems; work with databases (preferred MongoDB) and deploy to web servers (preferred IIS).

Lead design, development, integration, and support of Oracle Cloud ERP and EPM solutions. Architect scalable integrations, build OTBI/BI Publisher reports and APEX apps, provide L2/L3 production support, lead technical design and governance, and ensure compliance and performance optimization across finance and procurement processes.

Pipeline for software engineering roles at multiple levels. Work may include design, development, testing of embedded or application software, firmware and hardware-software integration, code review, debugging, performance optimization, Agile/Scrum practices, and cross-functional collaboration with systems, controls, and hardware teams.

Seeking a Senior Software Engineer with 5+ years of experience to design and develop large-scale distributed systems, mentor junior engineers, and manage complex projects in a dynamic setting.

Lead test architect for end-to-end integration testing of a complex genomics product portfolio. Design contract-first validations (OpenAPI/Avro), build resilient API and event-driven test frameworks, embed LLM-driven test generation and log analysis into CI/CD, mentor SQEs, enforce staging guardrails, and run chaos/resiliency experiments across distributed microservices.

Lead design and operation of a massively distributed edge compute platform using hyperscaler services and Kubernetes. Design external APIs, optimize L7 traffic routing, ensure high availability, fault tolerance, security and data privacy. Collaborate across AI/ML, hardware, network, and security teams, present scalability and reliability metrics to executives, mentor engineers, and establish architectural governance.

Lead Elasticsearch performance engineering from architecture through production. Develop performance models, optimize distributed systems, profile bottlenecks, build benchmarks, detect regressions, and improve scalability across stateful and serverless architectures. Design AI-assisted optimization and benchmarking tools, collaborate across teams, define performance strategies, and mentor engineers. The role requires deep Java, JVM, concurrency, distributed systems, and search or data-store performance expertise.

Develop and optimize Elasticsearch performance across distributed and serverless architectures. Responsibilities include implementing performance models, profiling systems, identifying bottlenecks, building benchmarks and regression detection, improving logging, metrics, vector search, and ES|QL performance, and creating AI-assisted optimization tools. The role also involves architectural and code-level optimization, technical analysis, peer reviews, and guidance for fellow engineers.

Lead strategic build-versus-buy engineering initiatives within Elastic’s IT organization. Design and deliver internal platforms using Elasticsearch, Kibana, Elastic ML, AI, and cloud technologies across developer productivity, FinOps, IT service management, and enterprise efficiency. Establish architecture and engineering standards, partner cross-functionally with IT, Security, Platform Engineering, Finance, and other teams, and validate Elastic products through internal production systems.

Develop and operate high-throughput, low-latency telemetry pipelines and cloud services for Azure AI/HPC infrastructure. Build observability, monitoring, analytics, and automation capabilities; own architecture through deployment and operations; and lead incident response, root-cause analysis, reliability improvements, and operational readiness. Partner across engineering and platform teams, influence technical roadmaps, mentor engineers, and apply distributed systems, AI infrastructure, and cloud operations practices at hyperscale.

Designs and implements protocols and features for highly scalable distributed block storage, focusing on durability, availability, performance, reliability, and observability. Responsibilities include coding, optimization, debugging, design documentation, stakeholder collaboration, incident response, on-call operations, and mentoring engineers. The role requires expertise in C or C++, distributed systems, cloud backend development, multithreaded programming, and large-scale software delivery.

Lead technical strategy and architecture for Azure Storage geo-replication, data protection, failover orchestration, and business continuity. Drive cross-team delivery, operational excellence, telemetry, automation, AI-assisted operations, and represent the team in executive and customer engagements.

Design and develop software to onboard hardware accelerators and optimize storage datapaths for Azure Storage. Drive design, debugging, performance tuning, operations, and cross-team collaboration across research, compute, and storage to improve throughput, scale, reliability, and observability.

Design, implement, and operate core components of Azure Storage, focusing on metadata and data services for a hyperscale distributed file system. Build reliable, durable, and cost-efficient storage platforms using DPUs, optimize OS and networking (TCP/RDMA), participate in design, on-call DRI duties, and drive reliability and performance improvements.

Design and operate large-scale, AI-native cloud infrastructure (especially Kubernetes/AKS). Improve service quality, automate incident prevention/remediation, accelerate engineering productivity, and integrate AI tools into development workflows.

Leads the design, implementation, optimization, and support of highly scalable Azure Storage services. Responsibilities include end-to-end performance testing, benchmarking, automation, profiling, bottleneck and root-cause analysis across compute, storage, and networking layers, KPI definition, scaling recommendations, and operational incident response. The role collaborates across teams, drives project and release plans, supports reliable and secure services, and mentors engineers while participating in on-call responsibilities.

Design and deliver large-scale, resilient AI and Kubernetes infrastructure for hybrid environments. Implement, optimize, and maintain cloud-native, container orchestration solutions; integrate AI capabilities; participate in on-call rotations; mentor engineers and drive reliability, observability, and performance at scale.

Design, implement, and operate low-level components of Azure Storage distributed file systems. Define requirements, produce designs, write and reuse high-quality code, break down work, estimate tasks, and act as an on-call DRI to monitor and restore services. Drive reliability, performance, observability, and scalability improvements.

Design, implement, debug, and ship features for Azure Storage front end at cloud scale. Drive design, dependency identification, automation, reliability, observability, and on-call incident response while collaborating with stakeholders and mentoring engineers.

Design and deliver large-scale, cloud-native and AI-enabled Kubernetes/AKS solutions. Implement, optimize, and maintain Kubernetes components and container orchestration across Azure, on-prem, and edge. Integrate AI capabilities, participate in on-call rotations, mentor engineers, and collaborate cross-functionally to improve reliability, observability, performance, and operational consistency at scale.